Journal Information
Sensors (Sensors)
http://www.mdpi.com/journal/sensors
Impact Factor:
3.031
Publisher:
MDPI
ISSN:
1424-8220
Viewed:
10161
Tracked:
23
Call For Papers
Journal Open for Submission
https://susy.mdpi.com/user/manuscripts/upload/d63bcb6dc1e06bf5bde439da70e2815e?pre_hash_key=d29661cd8958cc923333f6a84ea31dc5

Special Issue Proposal - Open for Application
https://www.mdpi.com/journalproposal/sendproposalspecialissue/sensors

Sensors 2021 Young Investigator Award
Amount: 2000 CHF
Nomination deadline: 30 June 2021
https://www.mdpi.com/journal/sensors/awards/submit/1338

Sensors 2021 Ph.D. Thesis Award
Amount: 1000 CHF
Application deadline: 31 August 2021
https://www.mdpi.com/journal/sensors/awards/submit/1249

Detailed description of all awards:
https://www.mdpi.com/journal/sensors/awards

Sensors (ISSN 1424-8220) provides an advanced forum for the science and technology of sensor and its applications. It publishes reviews (including comprehensive reviews on the complete sensors products), regular research papers and short notes. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. The full experimental details must be provided so that the results can be reproduced. There are, in addition, three unique features of this journal:
    
Manuscripts regarding research proposals and research ideas are particularly welcome.
Electronic files and software providing full details of calculation and experimental procedures can be deposited as supplementary material.  
We also accept manuscripts regarding research projects financed with public funds in order that reach a broader audience.

Scope
    Physical sensors
    Chemical sensors
    Biosensors
    Lab-on-a-chip
    Remote sensors
    Sensor networks
    Smart/Intelligent sensors
    Sensor devices
    Sensor technology and application
    Sensing principles
    Optoelectronic and photonic sensors
    Optomechanical sensors
    Sensor arrays and Chemometrics
    Micro and nanosensors
    Internet of Things
    Signal processing, data fusion and deep learning in sensor systems
    Sensor interface
    Human-Computer Interaction
    Advanced materials for sensing
    Sensing systems
    MEMS/NEMS
    Localization and object tracking
    Sensing and imaging
    Image sensors
    Vision/camera based sensors
    Action recognition
    Machine/deep learning and artificial intelligence in sensing and imaging
    3D sensing
    Communications and signal processing
    Wearable sensors, devices and electronics
Last updated by Jayleen Chen in 2021-03-18
Special Issues
Special Issue on special issue on Advances in Optical Proximity Sensor Based Interferometry
Submission Date: 2021-05-30

link: https://www.mdpi.com/journal/sensors/special_issues/Optical_Proximity_Sensor Special Issue Information This Special Issue is devoted to the description of development, testing, and modeling of optical proximity sensors, fiber or in air, based on the interferometry technique. The passage detection of an object represents a widely diffused measurement in industrial applications, and it is typically implemented by light barriers or proximity sensors. Different techniques are employed for realizing proximity sensors, based on the measurement of electric or magnetic field (inductive or capacitive sensors), ultrasonic waves or through optical approaches. Optoelectronic detectors are widely diffused, because they do not require metal targets such as inductive sensors, and they are faster than capacitive ones. The optical sensor can be also very low-cost, and it typically shows a good spatial resolution when compared to ultrasound devices. We solicit original research papers and review articles in this Special Issue. This Special Issue aims to highlight recent advances in the theory and practice of optical proximity sensors. The topics include but are not limited to: Development of novel optical proximity sensors based on interferometry, in air or fiber-based; Theoretical advancements in interferometric technique that can be used in proximity sensors; Measurement and comparison of the performances of different optical proximity sensors based on interferometry; Measurement and comparison of the performances of different optical proximity sensors based on interferometry with others based on different techniques; Theoretical simulation of different interferometric configuration for optical proximity detection; Different application for optical proximity sensors. Prof. Dr. Alessandro Pesatori (Politecnico di Milano) Guest Editor
Last updated by Vicky Cai in 2020-12-31
Special Issue on Advanced Fiber Photonic Devices and Sensors
Submission Date: 2021-05-31

https://www.mdpi.com/journal/sensors/special_issues/AFPDS Structured optical fibers such as photonic crystal fibers, multicore fibers, and microfibers have attracted intense interest and have been widely used in lasers, telecommunications, and sensing applications. The structural freedom of these types of specialty optical fibers opens up new sensing applications. The development of advanced fiber photonic devices and technologies is key to supporting their potential industrial applications. This Special Issue is addressed but not limited to the topics below. Original papers, letters and reviews are all welcome. Interconnects of specialty optical fibers; Coupling mechanism and devices of structured optical fibers; Polarization devices of structured optical fibers; Photonic crystal fiber sensors; Optical microfiber sensors; Multicore fiber sensors; Fiber-based Internet of Things. Prof. Dr. Limin Xiao Dr. Sergio G. Leon-Saval Dr. Tijmen G. Euser Guest Editors
Last updated by Daisy Wang in 2020-12-31
Special Issue on Intelligent Sensing in Biomedical Applications
Submission Date: 2021-05-31

https://www.mdpi.com/journal/sensors/special_issues/ISBAs At present, monitoring the course of the disease and the effect of therapy in clinical practice mostly depends on clinical scales and clinical impression. Such a description of the development of the patient’s condition is subject to intra-individual and inter-individual variability. In addition, such monitoring takes place only for a short time, mostly in the unnatural conditions of medical facilities. On the other hand, modern sensors enable increasingly accurate long-term monitoring of many important quantities. Reducing the variability of patient follow-up makes it possible to reduce the number of subjects in clinical trials and thus significantly reduce the cost of the studies. It also reduces the likelihood of false-negative results, thus saving the cost of developing new treatments. Smart sensor devices make it possible to acquire, process, and transmit data to users. Smart implants like orthopedic implants instrumented with strain gauges increase their lifespan. Retina implant systems using image sensors restore vision. Wearable body sensor networks comprising various types of sensors can monitor the course of vital variables for a long time, as well as the signal needed for therapeutic intervention. Biosensors enable the monitoring of physical activities. Results of machine learning methods contribute to the diagnosis of neurological disorders and the detection of tissue changes. This Special Issue is addressed to all types of smart sensors designed for biomedical applications. The topic of this Special Issue concerns the following areas of interest of the magazine: biosensors, sensor networks, smart/intelligent sensors, signal processing, data fusion, and deep learning in sensor systems. Dr. Oldřich Vyšata Prof. Dr. Aleš Procházka Dr. Rafael Doležal Guest Editors
Last updated by Daisy Wang in 2020-12-31
Special Issue on Sensing and Imaging Technology in Dentistry
Submission Date: 2021-05-31

https://www.mdpi.com/journal/sensors/special_issues/SITD Recent developments in sensing and imaging technologies have made a huge impact on the dental field. This impact involves technology applications from the research benchtop to the clinical chairside, and at times both. Today, dental imaging and sensing tools in clinical dentistry range from applications in the phases of diagnosis and treatment planning to the phases of implementation, monitoring, and maintenance using optical and X-ray sensors in various dental fields; general dentistry, preventive dentistry, operative dentistry, public health, periodontics, prosthodontics, endodontics, oral surgery, oral medicine, pathology, oral and maxillofacial radiology, and orthodontics. Non-destructive testing and imaging technologies have improved our understanding of dental material–tissue interactions in the dental field, particularly recent high-resolution three-dimensional computer tomography techniques. Following the success of our Sensors Special Issue on “Sensors in Dentistry”, we would like to once again invite our colleagues from across the world to contribute their expertise, insights, and findings in the form of original research articles and reviews for the current Special Issue, entitled “Sensing and Imaging Technology in Dentistry”. This issue will continue to cover all aspects of clinical and research applications of sensing technologies operating in any region of the electromagnetic spectrum in the field of dentistry. Special attention will be given to 3D and tomographic imaging techniques in the dental field, including but not limited to optical coherence tomography, micro-computed tomography, intraoral optical sensors, and scanners. Articles focusing on the development of other cutting-edge sensors and detectors for intraoral use, particularly early detection, are also welcome. Dr. Alireza Sadr Dr. Yasushi Shimada Dr. Turki A. Bakhsh Guest Editors
Last updated by Daisy Wang in 2020-12-31
Special Issue on Distributed Optical Fiber Sensors: Applications and Technology
Submission Date: 2021-05-31

https://www.mdpi.com/journal/sensors/special_issues/distributed_optical_fiber_sensors One of the key advantages of optical fiber sensors is their ability to perform distributed measurements, where small fiber sections act as individual gauges. Once founded as a relatively simple tool for inspection of optical fiber communication lines, this is currently one of the most rapidly developing areas of photonics with applications ranging from the oil and gas industry to biomedical inspection with sub-mm spatial resolutions. The Special Issue will focus on novel applications as well as the aspects of signal processing and physical principles of distributed optical fiber sensing. The main aim is to cover the diversity of the sensing principles and applications as widely as possible. The topic of this special issue is in accordance with the scope of the Sensors journal, as it will focus on various aspects of one of the most promising directions of research in the sensors community—distributed optical fiber sensors. While this field is mature enough to have already drawn considerable attention from researchers around the world, it is still evolving at a rapid rate, with new principles and applications being proposed on a regular basis. Dr. Nikolai Ushakov Dr. Leonid B. Liokumovich Dr. Arthur H. Hartog Guest Editors
Last updated by Daisy Wang in 2020-12-31
Special Issue on Special Issue "Nanoparticles-Based Sensors"
Submission Date: 2021-05-31

https://www.mdpi.com/journal/sensors/special_issues/Nanoparticles_Based_Sensors Dear Colleagues, One of the major challenges to be resolved by researchers is the design and development of reliable high sensitivity and low-cost sensors using novel nanoparticulate materials. The low dimensionality of nanoparticles results in excellent physicochemical properties (e.g., ease of functionalization via simple chemistry and high surface-to-volume ratios) which, allied with their unique spectral and optical properties, have prompted the development of a plethora of (bio)sensing platforms. Particularly, the incorporation of nanoparticulate materials in electrochemical devices notably provides benefits such as large specific surface area, high electrical conductivity, and low charge transfer resistance, which considerably improves electroanalytical properties such as high sensitivity and low limits of detection, among others. Nanoparticle-based sensors are gaining advantages in low cost point-of-care analysis of real samples, which involves complex sample matrices and even the need for wireless communications. For that reason, this Special Issue is intended to provide the most recent research results and emerging concepts in the challenging world of nanoparticles-based (bio)electrochemical sensors. The Special issue faces facile, sustainable scalable fabrication of nanostructured surface-based sensors using cutting-edge techniques such as screen or 3D printing technologies, looking for improving selectivity, fast response, long-term stability, and biocompatibility. Applications of nanomaterial-modified sensors for detection of relevant compounds in different fields such as the environment, clinical diagnostics, food quality control, and biowarfare are also welcome. Research papers, short communications, letters, and reviews will be considered for publication. Therefore, potential topics include but are not limited to the following: Synthesis and characterization of novel nanostructured materials for (bio)sensing applications; Stability and selectivity of composite nanoparticles in complex media; Long-term stability without regular maintenance; New insights in synergistic phenomena in terms of sensing properties; Applications of nanoparticle-based (bio)sensors. Prof. Dr. Edelmira Valero Prof. Dr. Jesús Iniesta Guest Editors
Last updated by Jayleen Chen in 2021-03-18
Special Issue on Special Issue "Advanced Management of Fog/Edge Networks and IoT Sensors Devices"
Submission Date: 2021-05-31

https://www.mdpi.com/journal/sensors/special_issues/fog_networks_IoT_sensor Dear Colleagues, Currently, an efficient interplay of the different computing and storage capabilities of Fog/Edge networks and IoT sensor devices is a fundamental challenge that needs to be overcome in order to give rise to the highly-demanded integrated services. In spite of the advances in the separate areas of Fog/Edge Networks (typically associated with Cloud infrastructures) and IoT sensor devices, research in the interplay between these areas is still in its initial stages, and we have a long way to go to achieve their global management and harnessing. Particularly, the incorporation and design of intelligent strategies in the management, analysis, and use of the interconnection and planning of networks by Soft-Computing, Big Data or Machine Learning must be regarded as especially important for a deep transformation of and advancement in current associated technologies. The objective of this Special Issue is to support the study, analysis, and implementation of diverse enabling advances in the field of Fog/Edge networks and IoT sensor devices and their interconnection, such as the improvement of virtualization of applications and microservices in IoT sensor devices and Fog/Edge systems, the compatible integration of containers with the main function and performance of containers in IoT sensor devices and Fog/Edge equipment, the security in Fog/Edge and IoT device transactions with Blockchain technology, the improvement of lightweight virtualization systems for deployment in low-performance nodes, such as sensor devices of Fog/Edge networks and IoT or end users, energy reduction in the different layers of a Fog/Edge and IoT network through knowledge-based strategies, accelerating workflow processing in Fog systems, distributed data storage and Big Data tools, intelligent scheduling for container allocation, etc. Topics to be covered include but are not limited to the following: IoT sensor devices Fog Computing Edge Computing Cloud Computing Fog/Edge and IoT Networks Interplay Content delivery networks Soft-computing Big Data Machine learning Virtualization Containers Scheduling Blockchain Energy consumption in computing distributed networks Latency-aware application in distributed networks Dr. Rocío Pérez de Prado Guest Editor
Last updated by Jayleen Chen in 2021-03-18
Special Issue on Vehicle-to-Everything (V2X) Communications
Submission Date: 2021-06-10

Dear Colleagues, Over the last few years, there have been a large number of advancements in communication and computation technologies, and many of these technologies are being embedded in the vehicles of the future. These vehicles, dubbed “networks-on-wheels”, are able to communicate with various elements of intelligent transportation systems, including pedestrians, vehicles, and infrastructure, and hence led to the term vehicle-to-everything (V2X). Whether based on cellular networks or dedicated short-range communications (DSRC), V2X is the main enabler for advanced driver assistance systems (ADAS), and has the potential to make the transportation system safer, more efficient, and more environmentally friendly. This Special Issue of the Sensors magazine looks at recent research and developments in the area of V2X, as well the remaining challenges and road blocks. Dr. Khalil El-Khatib Guest Editor Keywords Intelligent vehicles Intelligent transportation systems 5G mobile communication Vehicle-to-vehicle communication V2X communications Vehicle safety Vehicular ad hoc networks Mobility management Sensors (ISSN 1424-8220, IF 3.275) is the leading open-access journal on the science and technology of sensors, launched 20 years ago. More than 10,200 articles have been cited 10 times or more. Sensors’ 2019 impact factor is 3.275 (5-year impact factor: 3.427). It ranks in Q1 in the JCR category of Instruments & Instrumentation. The CiteScore (2019 Scopus data) of Sensors is 5.0. To submit to the journal click here:http://susy.mdpi.com/user/manuscripts/upload?journal=sensors. Should you have any questions, please feel free to contact jason.liu@mdpi.com.
Last updated by Jason Liu in 2021-02-22
Special Issue on Special Issue "IoT and Artificial Intelligence Approaches to Defeat COVID-19 Outbreak"
Submission Date: 2021-06-15

https://www.mdpi.com/journal/sensors/special_issues/AI_outbreak Dear Colleagues, Sensors provide valuable data about physical devices and the associated environment. The unprecedented increase in data volumes related to different sensor applications and networks is powering big data analytics through a range of artificial intelligence (AI) techniques. In the context of COVID-19, big data refers to patient healthcare data such as lists of physicians and patients, medical images, physician notes, case history, chest X-ray reports, information about outbreak areas, and so on. These data are generated from a number of sources, ranging from Internet of Things (IoT) sensors (e.g., smartphone data) to online social platforms (e.g., public reactions). The traditional data analytic tools and mechanisms are not adequate for meeting the requirements during the COVID-19 pandemic. For example, two of the new research directions with COVID-19 involve using AI techniques for medical image processing and sentiment analysis toward social distancing. The translation of these big data into concrete actions (e.g., deriving valuable information from people’s opinions toward social distancing measures) requires processing the inputs acquired from sensors and social networks. Such transformation and processing can benefit from the new insights provided by branches of AI, like the use of machine learning and deep learning to improve the COVID-19 pandemic situation and drive further mitigation of the COVID-19 outbreak. Authors of selected high-qualified papers from the International Workshop on Security, Privacy, and Trust for Emergency Events (EmergencyComm 2020) will be invited to submit extended versions of their original papers (50% extensions of the contents of the conference paper) and contributions. Topics of interest include but are not limited to: COVID-19 crisis management and communication strategies; Security, privacy, and trust practices to address events like the COVID-19 outbreak through data from social and IoT networks; Sentiment analysis toward social distancing against COVID-19; AI to process COVID-19 data from IoT sensor networks; AI techniques for medical image processing for COVID-19; Automated messaging to deliver timely and relevant prevention messages against COVID-19; Identifying and blocking scams and other cybercrime tactics involving COVID-19; Measuring community acceptance of social distancing against COVID-19; The role of messaging and chatbots in engaging concerned users; Privacy-preserving data mining and machine learning for emergency events through IoT ; Modelling and protection of the disease spread and other hazardous consequences; Understanding risks associated with coronavirus infections through AI-based sensor applications; and Identifying social distancing parameters through deep learning architectures along with data from IoT sensor networks Dr. A.S.M. Kayes Prof. Dr. Paul Watters Dr. Ebrima Ceesay Dr. Man Qi Dr. Md. Saiful Islam Dr. Abdur Rahman Bin Shahid Guest Editors
Last updated by Jayleen Chen in 2021-03-18
Special Issue on special issue on Smart Sensors for Wearable Applications
Submission Date: 2021-06-20

link: https://www.mdpi.com/journal/sensors/special_issues/Sensors_Wearable_Applications Special Issue Information The evolution of the Internet of Things (IoT) has enabled the emergence of compact and conformal devices that could be embedded in individual bodies, revolutionizing the way we interact with the world and augmenting our quality of life. These devices are known as smart wearable or mobile health technology devices. They come in different form factors of body-worn objects, such as watches, glasses, clothing, and even tattoo-like patches using advanced developments in the area of flexible/stretchable electronics. The diversity and innovation of new materials, form factor, and design as well as the integration of information coming from different smart sensors is key to expanding the potential of the application of mobile health technology. Applications are limitless and span the fields of environmental monitoring, prosthetics & robotics, healthcare and wellness, biomedical systems, ocean health study, fitness tracking, sports and wellness, mobile gaming, etc. This Special Issue is intended to report recent advances in the multidisciplinary field of wearable sensing technologies. Articles will address topics that include smart sensors, wearable sensing technologies, smart textiles, smart materials, implantable sensors, flexible and stretchable sensors, energy harvesting in wearables, as well as low-power data acquisition and data transmission in support of smart sensors in Internet of Things applications. A discussion on the challenges and gaps that still remain to achieve desired characteristics and performance from wearable sensors is desired. We aim to report innovation in research but also help clarify necessary steps still needed for practical translation to the hands of the consumer. Keywords Mobile health technology Wearable technology Smart sensors Flexible and stretchable sensors Optic sensors Integrative mobile technology Clinical and imaging correlation of digital data E-skin Healthcare and wellness Internet of Things (IoT) Environmental Monitoring Robotics Mobile gaming Brain mapping Dr. Andrea Pilotto (Dipartimento di Scienze Cliniche e Sperimentali, University of Brescia) Dr. Joanna Nassar (Department of Biology,Stanford University) Guest Editors
Last updated by Vicky Cai in 2020-12-31
Special Issue on special issue on Sensing and Monitoring Electric and Electromagnetic Quantities in Railways
Submission Date: 2021-06-20

link: https://www.mdpi.com/journal/sensors/special_issues/Electric_Sensing_Railways Special Issue Information Measurement and monitoring of electrical and electromagnetic quantities in railways has always been an important part of the whole assessment of correct operation of the supply circuit, rolling stock, signaling, and control. The new challenges for sustainable mobility, for impact on third parties, and for high levels of reliability and continuity of service require the development and deployment of new monitoring architectures, integrating various types of smart sensing technologies: Resulting architectures may extend over the entire transportation system, being integrated with the existing infrastructure and exploiting interconnection and data exchange offered by modern communication means, as well as power harvesting. More traditional applications cover power quality and compatibility with signaling and control systems. Examples of more recent applications range from the monitoring and quantification of the energy efficiency of the whole system (installing sensing units both on-board trains and in supply substations) to fostering predictive maintenance of the current collection system (with existing applications for catenary–pantograph contact quality covering a wide range of physical quantities, with a tendency to integrate modern energy meters with additional monitoring functions). Other applications may focus on the track, monitoring stray current, and corrosion (with challenges of data analysis on different time scales, depending also on the characteristics of the environmental and service conditions), as well as verifying the physical integrity of the track (exploiting existing signaling circuits, or using magnetic, traveling wave or ultrasound excitation). This Special Issue thus cordially invites contributions on electrical and electromagnetic sensors, smart sensors and measurement, and monitoring architectures for railways. Keywords voltage sensor current sensor energy efficiency power quality stray current stray current control pantograph arcing rail diagnostic sensor architecture Dr. Domenico Giordano (National Institute of Metrological Research) Prof. Dr. Andrea Mariscotti (DITEN, University of Genova) Guest Editors
Last updated by Vicky Cai in 2020-12-31
Special Issue on Special Issue on Sensors, Networks and Applications for Intelligent Monitoring of the Territory 
Submission Date: 2021-06-30

Special Issue on Sensors, Networks and Applications for Intelligent Monitoring of the Territory https://www.mdpi.com/journal/sensors/special_issues/Intelligent_monitoring_Territory Dear Colleagues, In recent years, the deployment of networks of sensors for the monitoring of territory has become an indispensable necessity for almost every country. An advanced system for environmental monitoring integrates data originating from different networks of sensors and Internet of Things (IoT) devices spared over the territory. Usually, each sensor network is tailored for the observation of one or a specific subset of phenomena to be kept under control, i.e., we have networks for monitoring landslides and/or floods from rivers, earthquakes, volcanoes activity, etc. In general, measurement sites including dataloggers, sensors, and IoT devices are scattered throughout the territory to be monitored at local, regional or national scale. In each site, the single datalogger uses wired and/or local radio technologies (e.g., Wi-Fi, Bluetooth LE, ZigBee), to communicate with sensors acquiring environmental data. In turn, the datalogger connects to the (specific) communication infrastructure serving the monitoring network for the transfer of environmental data to one or more territorial control centers (TCCs). Due to the relatively small amount of data to be collected on a periodical basis, existing monitoring networks are characterized by very low transmission bit rates towards the TCC (i.e., from bit/s to some kbit/s), which we can refer to as “narrowband” monitoring networks. The possibility of providing the TCC with environmental audio, FHD/4K/8K videos, and/or images (in the visible and/or infrared ranges) from the observation sites would require a design of new sensor devices as well as to re-think the communication infrastructure to be associated with the innovative “broadband” monitoring network. The availability of these “new” types of data allows improving the performance of the analysis and prediction algorithms used to assess the status of the environment and to ease the detection of anomalous/critical/emergency situations. Furthermore, “multimedia” information on the occurrence of anomalous events, provided by people recording video/audio contents with their smartphones, has now become customary and could be seen as a sort of “casual” additional source of information on the environment to be exploited in some way. In particular, innovative machine learning and artificial intelligence algorithms should integrate information from “social networks” (when available) with those from the narrowband/broadband monitoring networks in order to further support the detection of anomalous situations in a specific area. In addition, when properly managed and checked, information from “socials” could provide authorities with a preliminary view of the status of a declared emergency area even before the arrival of first responders. In the case of emergency, communications from authorities and organizations to individuals, groups or the general public are based on the emergency warning systems including a multitude of technologies, such as mobile phones, location-based alerting using short message service, email, TV, radio, etc. Integration of the TCCs with the emergency warning system for fast alerting the population is an important aspect involving many technical and organizational issues. Potential topics in this Special Issue include, but are not limited to: Innovative, collaborative, and advanced “broadband” monitoring networks for territory including water monitoring, glacier monitoring, landslide monitoring, atmosphere monitoring, and so on; Aerial monitoring solutions including unmanned aerial systems (UAS); Solutions for communication networks for the transport of monitored data on a local, regional, national scale: public and private terrestrial networks, LEO/MEO/GEO satellites; Reliability, planning, and dimensioning of innovative monitoring networks; Technologies for sensors, IoT devices, and UAS for the acquisition of environmental data even including multimedia data formats and/or information from social networks and social media; Quality assurance and quality control of measurements; GNSS accurate localization techniques for geo-tagging and for timestamp of data; Machine learning, artificial intelligence, and big data algorithms for environmental data analysis and for reliable detection of anomalous and critical situations; Expert systems and decision support systems (DSS) for emergency warning; Cost analysis of innovative and advanced monitoring networks and applications. Innovative business models; Security aspects of monitoring networks and their applications. Guest Editors Prof. Franco Mazzenga Prof. Romeo Giuliano Dr. Alessandro Vizzarri
Last updated by Silvia Li in 2021-04-25
Special Issue on Special issue on Unmanned Aerial Vehicles for Future Networking Applications
Submission Date: 2021-06-30

Special issue on Unmanned Aerial Vehicles for Future Networking Applications https://www.mdpi.com/journal/sensors/special_issues/uav_future_networking_applications Dear Colleagues, Advances in unmanned aerial vehicles (UAV) are enabling the development of a myriad new UAV-based systems which could not even be imagined some years ago. There are numerous possibilities, but of particular interest is the usage of UAVs to support future networking applications, for example, creating network infrastructure on-demand, which can be provisioned and released according to the current application needs. The emerging Internet of Things (IoT)-based applications, with massive distributed sensors, can benefit a lot from the employment of such UAV-based support. With the advance of 5G, 6G, and beyond technologies, this usage of UAV-based systems gains even more importance, as the number of possible beneficial applications grows significantly. The goal of this Special Issue is to address this emerging field in which UAVs can be used to support future networking applications. Topics of interest include but are not limited to the following: Novel applications of UAVs; Deploying UAV as a base station for 5G systems; Role of UAVs in 6G systems; On-demand wireless networking infrastructure; Massive distributed applications; Applications of UAVs for lifeline communications; Development of edge computing systems for UAVs; Offloading models and algorithms for UAV applications; UAVs to assist AR/VR systems; Deploying emerging technologies, e.g., SDN and Blockchain, for UAV systems; Emerging IoT-based applications; Application of UAVs in remote sensing; Flying sensors; Space-terrestrial networks. Guest Editors Prof. Dr. Andrey Koucheryavy Prof. Dr. Edison Pignaton de Freitas Dr. Jiri Hosek
Last updated by Silvia Li in 2021-04-25
Special Issue on Wireless Sensor Networks towards the Internet of Things 
Submission Date: 2021-06-30

Dear Colleagues, Today, wireless sensor networks continue to be highly regarded by both academia and industry, involving a wide range of stakeholders such as researchers, industrialists, hardware manufacturers, and related IT services. The areas of application of WSNs are also increasing, ranging from simple monitoring to the medical, military, and welfare fields. Among the directions in which WSNs are moving, we cannot fail to mention the interactions between people and the nodes’ environment, the use of artificial intelligence traffic management, and the use of the IoT as an industrial tool. The integration and development of low-power WSN sensors in the IoT system will be a major evolution of WSN, and several research areas are still emerging from new needs and challenges. The purpose of this Special Issue is to assess WSN technology and characteristics, review WSN applications, and provide information on the challenges and future of WSNs with particular emphasis on their use from an Internet of Things perspective. A wide range of documents will be considered that present innovative approaches to the state-of-the-art, monitoring, and control of WSN with the introduction of the IoT, which allows a great variety of applications. The topics of interest for publication include but are not limited to: WSN standards and specifications; WSN architectures and protocol stack; WSN IoT development platforms; WSN IoT data management; Sensor node and energy optimization; WSN and artificial intelligence; WSN for smart cities applications; WSN data privacy and security; WSN and Industry 4.0; Multihop routing and WSN energy efficiency. Dr. Matteo Anedda Prof. Dr. Daniele Giusto Guest Editors
Last updated by Jane Xu in 2021-04-25
Special Issue on Nanostructured Materials Systems for Optical Sensing
Submission Date: 2021-06-30

Dear Colleagues, Nanotechnology has demonstrated great potential in the preparation of new nanostructured materials with different properties, new functions, and added value. Numerous studies have been carried out with the aim to improve the properties and performance of optical functional materials through the application of nanocomposites, metallic nanoparticles or carbon materials. Over the last decade, optical-sensing-based nanostructured materials have arisen as a key research topic in both fundamental and applied sciences. It is known that the optical response of nanostructured materials depends on their environment, namely, pressure, temperature, pH, and humidity, resulting in sensor materials with increased sensitivities, multiplexing capabilities, and high efficiency in detecting and monitoring chemical or biological molecules. For example, the use of surface plasmon resonances in metallic nanostructured particles for surface enhanced Raman scattering (SERS) applications has gain special interest, in the last years. This is fundamentally due to two reasons: the technological evolution observed at the level of Raman's equipment and the development of techniques/methods to enhanced the molecular probe's signal using nanostructured materials. This Special Issue is addressed at all types of nanostructured materials that can be applied in optical sensing and detection of biomolecules, aiming to collect the latest trends and progress in the field of “Nanostructured Materials for Optical Sensing”. Dr. Sara Fateixa Guest Editor
Last updated by Jane Xu in 2021-04-25
Special Issue on Context-Aware Computing Based on Mobile Sensing
Submission Date: 2021-06-30

Recent advancements in mobile and ubiquitous computing have enabled the development of novel, context-aware computing applications. Additionally, the fusion of inexpensive and widely available hardware with advances in artificial intelligence have made practical context-aware computing widely accessible, e.g., in the form of intelligent assistants, smart thermostats, and mobile app-embedded functionality. This Special Issue examines the state of the art in context-aware computing and also takes a look into the future, focusing on technologies and applications that are envisioned to advance the sector even further. The potential topics include, but are not limited to, the following: Data sensing and data management for context-aware computing Algorithms for data processing and inferring in context-aware computing Theory, models, and algorithms for context-aware computing Software engineering models, methods, and tools for context-aware computing Context-aware mobile and ubiquitous computing Context-aware IoT systems Context-awareness in autonomous systems/robotics Context-aware computing in smart cities Edge-/fog-/cloud-based architectures for enabling context-aware computing Context-aware adaptive systems Context recognition and context prediction Context fusion/alignment Crowdsourcing platforms for context retrieval Machine learning and artificial intelligence in context-aware computing Indoor and outdoor positioning systems Applications of context-aware computing Novel sources and datasets of context data Privacy and security concerns for context-aware computing Socio-technical concerns, ethics, and responsible design in context-aware computing applications Prof. Dr. Kurt Geihs Prof. Dr. Romain Rouvoy Dr. Nearchos Paspallis Guest Editors
Last updated by Jane Xu in 2021-04-25
Special Issue on Context-Aware Computing Based on Mobile Sensing
Submission Date: 2021-06-30

https://www.mdpi.com/journal/sensors/special_issues/cacms_sensors Recent advancements in mobile and ubiquitous computing have enabled the development of novel, context-aware computing applications. Additionally, the fusion of inexpensive and widely available hardware with advances in artificial intelligence have made practical context-aware computing widely accessible, e.g., in the form of intelligent assistants, smart thermostats, and mobile app-embedded functionality. This Special Issue examines the state of the art in context-aware computing and also takes a look into the future, focusing on technologies and applications that are envisioned to advance the sector even further. The potential topics include, but are not limited to, the following: Data sensing and data management for context-aware computing Algorithms for data processing and inferring in context-aware computing Theory, models, and algorithms for context-aware computing Software engineering models, methods, and tools for context-aware computing Context-aware mobile and ubiquitous computing Context-aware IoT systems Context-awareness in autonomous systems/robotics Context-aware computing in smart cities Edge-/fog-/cloud-based architectures for enabling context-aware computing Context-aware adaptive systems Context recognition and context prediction Context fusion/alignment Crowdsourcing platforms for context retrieval Machine learning and artificial intelligence in context-aware computing Indoor and outdoor positioning systems Applications of context-aware computing Novel sources and datasets of context data Privacy and security concerns for context-aware computing Socio-technical concerns, ethics, and responsible design in context-aware computing applications Prof. Dr. Kurt Geihs Prof. Dr. Romain Rouvoy Dr. Nearchos Paspallis Guest Editors
Last updated by Jane Xu in 2021-04-25
Special Issue on Wireless Sensor Networks towards the Internet of Things
Submission Date: 2021-06-30

https://www.mdpi.com/journal/sensors/special_issues/wsniot_sensors Dear Colleagues, Today, wireless sensor networks continue to be highly regarded by both academia and industry, involving a wide range of stakeholders such as researchers, industrialists, hardware manufacturers, and related IT services. The areas of application of WSNs are also increasing, ranging from simple monitoring to the medical, military, and welfare fields. Among the directions in which WSNs are moving, we cannot fail to mention the interactions between people and the nodes’ environment, the use of artificial intelligence traffic management, and the use of the IoT as an industrial tool. The integration and development of low-power WSN sensors in the IoT system will be a major evolution of WSN, and several research areas are still emerging from new needs and challenges. The purpose of this Special Issue is to assess WSN technology and characteristics, review WSN applications, and provide information on the challenges and future of WSNs with particular emphasis on their use from an Internet of Things perspective. A wide range of documents will be considered that present innovative approaches to the state-of-the-art, monitoring, and control of WSN with the introduction of the IoT, which allows a great variety of applications. The topics of interest for publication include but are not limited to: WSN standards and specifications; WSN architectures and protocol stack; WSN IoT development platforms; WSN IoT data management; Sensor node and energy optimization; WSN and artificial intelligence; WSN for smart cities applications; WSN data privacy and security; WSN and Industry 4.0; Multihop routing and WSN energy efficiency. Dr. Matteo Anedda Prof. Dr. Daniele Giusto Guest Editors
Last updated by Jane Xu in 2021-04-25
Special Issue on Nanostructured Materials Systems for Optical Sensing
Submission Date: 2021-06-30

https://www.mdpi.com/journal/sensors/special_issues/NMSOS_sensors Dear Colleagues, Nanotechnology has demonstrated great potential in the preparation of new nanostructured materials with different properties, new functions, and added value. Numerous studies have been carried out with the aim to improve the properties and performance of optical functional materials through the application of nanocomposites, metallic nanoparticles or carbon materials. Over the last decade, optical-sensing-based nanostructured materials have arisen as a key research topic in both fundamental and applied sciences. It is known that the optical response of nanostructured materials depends on their environment, namely, pressure, temperature, pH, and humidity, resulting in sensor materials with increased sensitivities, multiplexing capabilities, and high efficiency in detecting and monitoring chemical or biological molecules. For example, the use of surface plasmon resonances in metallic nanostructured particles for surface enhanced Raman scattering (SERS) applications has gain special interest, in the last years. This is fundamentally due to two reasons: the technological evolution observed at the level of Raman's equipment and the development of techniques/methods to enhanced the molecular probe's signal using nanostructured materials. This Special Issue is addressed at all types of nanostructured materials that can be applied in optical sensing and detection of biomolecules, aiming to collect the latest trends and progress in the field of “Nanostructured Materials for Optical Sensing”. Dr. Sara Fateixa Guest Editor
Last updated by Jane Xu in 2021-04-25
Special Issue on Remote Sensing and GIS Applications on Groundwater Research
Submission Date: 2021-06-30

https://www.mdpi.com/journal/sensors/special_issues/RSGAGR_sensors Dear Colleagues, Groundwater is one of the most important natural resources because, in many regions, it is the main source of water supply, essential for human activities, economic development, and environmental conservation. Groundwater has several relevant advantages compared with surface water: it is less affected by evaporation, is available over large regions, and normally is of higher quality and more protected from possible pollution. Those are precisely the reasons why it is essential to apply innovative tools to obtain more detailed and real-time knowledge of the actual situation of groundwater, to facilitate appropriate management and water protection activities. In that sense, remote sensing is a technology that provides useful groundwater indicator data, in a more efficient and less costly way than invasive methods. Furthermore, the obtained data can be integrated into geographic information systems (GIS), which are innovative technologies that have a paramount role in spatial analysis, geostatistical techniques, and numerical modeling. This Special Issue of Sensors will present the latest advances in the application of remote sensing and GIS data analysis in the field of groundwater research and management. We invite contributions that address every aspect of remote sensing and GIS related to the following research issues: Hidrogeological mapping Soil moisture monitoring Assessment of natural and artificial groundwater recharge Submarine groundwater discharge (SGD) evaluation Assessment of groundwater use in irrigated agriculture Groundwater–surface water interaction GIS-based groundwater management Keywords Groundwater Remote sensing GIS Groundwater management Groundwater recharge Aquifer vulnerability Submarine groundwater discharge (SGD) Groundwater–surface water interaction Aquifer vulnerability assessment Prof. Dr. Francisco Conde Guest Editor
Last updated by Jane Xu in 2021-04-25
Special Issue on special issue on UAV-Based Technology for IoT
Submission Date: 2021-06-30

link: https://www.mdpi.com/journal/sensors/special_issues/UAV_IOT Special Issue Information As ubiquitous connectivity and long-range radio coverage are required in many emerging Internet of Things (IoT) applications in multidisciplinary fields, supplementing and extending the terrestrial and satellite communication infrastructure is of paramount importance. In this respect, unmanned aerial vehicles (UAVs) are a promising candidate technology for attaining highly reliable and effective connections between sensors and data collection points at high elevation angles and across urban, suburban, and rural terrains. Nevertheless, there exist several scientific and technical challenges for enabling the successful and long-term operation of UAV-based IoT for both massive machine type communications (mMTC)-based and ultra-reliable/low-latency communications (URLLC)-based delay-sensitive scenarios. To meet the mMTC and URLLC presuppositions in highly dynamic and heterogeneous environments, where the UAVs act as autonomous communicating nodes or aerial relays, advanced sensor, antenna, communication, networking, and computing technologies should be proposed, revised, and developed. This ambiguous landscape regarding UAVs and IoT has motivated the present Special Issue, whose aim is to introduce current research activities and prospective solutions towards the evolution of UAV-based IoT technologies. Therefore, potential authors are invited to submit original research articles or surveys, new developments, and substantial experimental works. Topics of interest include (but are not limited to) the following: Sensor and actuator technologies Navigation, detection, and localization systems Network architectures and protocols Channel modeling and measurement Wireless communication technologies, e.g., mmWave, massive multiple input multiple output (MIMO), non-orthogonal multiple access (NOMA), free-space optical (FSO) Interference and resource management Energy harvesting and wireless power transmission Trajectory optimization Mobile edge computing (MEC) Software-defined radio (SDR), software-defined networking (SDN), and network function virtualization (NFV) Machine learning and deep learning methods Safety, security, and privacy issues Prototype results, testbeds, and new applications Dr. Emmanouel T. Michailidis (Department of Electrical and Electronics Engineering, Faculty of Engineering, University of West Attica) Prof. Dr. Petros S. Bithas (General Department, National and Kapodistrian University of Athens) Guest Editors
Last updated by Vicky Cai in 2020-12-31
Special Issue on Surface Plasmon Sensors
Submission Date: 2021-06-30

https://www.mdpi.com/journal/sensors/special_issues/surface_plasmon_sensors In recent years, basic and applied research on surface plasmon resonance (SPR) has been actively conducted. In particular, the SPR sensor is one of the devices that has been actively investigated in applied research of an optical platform using the propagation of surface plasmon polaritons. The utilization of nanostructures has enabled the development of more sensitive detection formats adapted to multiplexed configurations. Specifically, the unique optical and electronic properties of nanomaterials have permitted the advancement of localized surface plasmon resonance (LSPR) and surface-enhanced raman scattering (SERS) applications. Likewise, the fabrication of nanopatterned structures through lithographic patterning has provided high spatial resolution surface structures while improving the sensitivity of the systems. In this Special Issue, we would like to compile the latest research results on the theory and experiments regarding the measurement principle, detection formats, performances, and applications for surface plasmon sensors, and to discuss the current status and future prospects of surface plasmon sensor performance. Dr. Atsushi Motogaito Prof. Dr. Elba Mauriz Guest Editors
Last updated by Daisy Wang in 2020-12-31
Special Issue on Wearable Sensors for Gait and Falls Monitoring
Submission Date: 2021-06-30

https://www.mdpi.com/journal/sensors/special_issues/WSGFM Falls and any resulting injuries and disabilities remain major public health concerns worldwide. The Global Burden of Diseases, Injuries and Risk Factors Study 2017 ranked falls as the 18th leading cause of age-standardized rates of disability worldwide. Gait analysis and falls go hand in hand, as abnormalities in the former often lead to the latter. Over the years there have been considerable advancements in health assessment technology using sensors coupled to the rise of big data. Such advances continue to drive important research on new applications for this technology to support the management of this major societal healthcare challenge. Yet more needs to be done. The ongoing COVID-19 pandemic and the resultant need for self-isolation and social distancing have presented new challenges to the delivery of effective healthcare remotely. Such challenges also create new opportunities. There is a need to develop newer and better technologies that can support digital transformation to be able to assess gait, predict and detect falls, reduce injury and facilitate the remote delivery of healthcare in newer and innovative ways and to reduce health inequity. This Special Issue of Sensors aims to promote and support leading research in this area. Prof. Dr. Michael Vassallo Prof. Dr. Hongnian Yu Prof. Dr. Yanhong Liu Dr. Arif Reza Anwary Guest Editors
Last updated by Daisy Wang in 2020-12-31
Special Issue on Multipixels Single Photon Detectors for Quantum Applications
Submission Date: 2021-06-30

https://www.mdpi.com/journal/sensors/special_issues/spd_sensors Non-classical states of light, as for instance entangled photons, promise dramatic improvements over classical optical methods, or even allow for novel measurement schemes. Recording efficiently their spatio-temporal properties requires sensors that combine high temporal and spatial resolution and high sensitivity. This special issue is addressed to all arrays of single photon detectors for quantum sensing and their applications. Dr. André Stefanov Dr. Leonardo Gasparini Guest Editors
Last updated by Daisy Wang in 2020-12-31
Special Issue on Distributed Optical Fiber Sensors for Concrete Structure Monitoring
Submission Date: 2021-06-30

https://www.mdpi.com/journal/sensors/special_issues/DOFSCSM Structural health monitoring (SHM) is a crucial process in the maintenance strategy for concrete infrastructures, as it enables real-time diagnosis of the integrity and the state of wear/damage of the structure. In this context, truly Distributed Fiber-Optic Sensor (DFOS) systems paired with an optoelectronic interrogator offer the possibility to record various measurands at thousands of locations along the fiber sensor, over long distances, and with a user-customizable spatial range down to the centimeter scale. This emerging technology is very promising for the SHM of large reinforced concrete structures, as it can provide both local/global information on material and structural characteristics like strain, temperature, sound, and vibration. Such information can then be analyzed to detect, localize, and quantify structural defects and degradation related to concrete pathologies, such as stress concentrations, crack onset and development, moisture, leakages, corrosion of steel rebars, creep, and shrinkage, and swelling pathologies, such as alkali–aggregate reactions and sulfate attacks. Nevertheless, extensive research efforts are needed to improve the monitoring performance of DFOSs, methods for assessing the reliability/accuracy of DFOS measurements with respect to the effective state of the host structure, the durability of DFOSs under service conditions (especially when embedded in an alkaline concrete medium or directly exposed to the outdoor environment), and post-processing methods for converting the huge quantity of data into relevant indicators for users and maintenance operators. For this Special Issue, we invite the submission of original research articles and reviews dedicated to recent developments in and research on experimental, practical, and theoretical aspects of the SHM of concrete structures using DOFS instrumentation. Potential topics include, but are not limited to: recent progress in distributed fiber-optic sensors (DFOS) in the field of civil engineering; structural health monitoring; distributed measurements based on Raman, Rayleigh, or Brillouin scattering; analysis of the strain response of DFOS; crack detection and quantitative evaluation of crack openings in concrete structures with DFOS; monitoring of concrete pathologies using DOFS; temperature measurements based on DFOS; decoupling of strain and temperature effects on the DFOS response; distributed acoustic sensors (DAS); corrosion monitoring sensors; distributed moisture sensing; coating and sensor packaging; sensing tapes; performance of DOFSs bonded to the surface of/embedded in concrete structures; durability under service conditions; aging behavior of DFOSs; reliability/uncertainty assessment of DOFS instrumentation; post-processing techniques for event detection and data interpretation based on automated signal analysis or Artificial Intelligence (AI) methods; and case studies and applications of DOFS instrumentation in the field. Dr. Karim Benzarti Dr. Marc Quiertant Dr. Jean-Marie Hénault Guest Editors
Last updated by Daisy Wang in 2020-12-31
Special Issue on Biomedical Sensing for Human Motion Monitoring
Submission Date: 2021-06-30

https://www.mdpi.com/journal/sensors/special_issues/BSHMM Recent advances in sensor technology mean that wearable sensors are available that can provide information similar to that which once required an expensive lab setup. In addition to reducing costs, taking movement recordings outside of the lab has many other advantages. It is possible to record physiological and biomechanical signals in more realistic situations, record changes in behavior observed throughout the day, better quantify the natural variability in behavior at different time scales and in response to different events, and to monitor behavior to identify special events such as falls in real time. These insights have the potential to improve healthcare outcomes by improving diagnosis, allowing the tracking of progress (e.g., exercise) and rehabilitation, providing large data sets for use in research studies, and providing real-time feedback to improve behavior and for safety purposes. In this Special Issue, we invite papers on topics related to new techniques, analyses, and feedback of recording and monitoring of human movements in different environments using a variety of biomedical sensors. Dr. Jason Friedman Dr. Sigal Portnoy Guest Editors
Last updated by Daisy Wang in 2020-12-31
Special Issue on Computer Vision Based Smart Sensing
Submission Date: 2021-07-15

https://www.mdpi.com/journal/sensors/special_issues/cvcss_Sensors Dear Colleagues, Sensing of visual information with video cameras has become an almost ubiquitous element of our environment. Internet connectivity and the massive use of the Internet of Things (IoT) has contributed to this in a very important way. The number of video cameras deployed with the capacity to capture information both in the visible range and outside the visible range (IR, UV, or other bands) has grown very significantly in recent years, with figures ranging from 50 to 150 surveillance cameras per 1000 inhabitants in the most important cities in Asia, Europe, and America. Moreover, this is only with regard to fixed surveillance cameras (on streets, roads, and buildings). If, in addition, mobile and wearable devices incorporating cameras are taken into account, the possibilities for capturing visual information are almost infinite. To be able to process such a large volume of information, it is necessary to develop computer vision applications for the different areas in which they are usually applied: security, health, multimodal transport, accessibility for people with disabilities of any kind, cultural heritage preservation, etc. The capacity for smart sensing with cameras has grown significantly with the application of deep learning strategies to images and video sequences. These applications usually have a high computing cost, which is encouraging the emergence of smart processing strategies: on the edge near the point of capture, distributed in the cloud, etc. In order to make these applications robust, it is usually necessary to provide them with certain self-calibration capabilities, resilience, or even the ability to fuse visual information with other devices, such as radars or LiDAR. This Special Issue aims to address the open research challenges and unsolved problems related to computer-vision-based smart sensing applications in different domains, making use of IoT-connected, camera-acquired information (inside the visible range or outside it) in an isolated way or by fusing them with other image-based devices, such as LiDAR or radar, in a monocular configuration or a multicamera one. Keywords smart computer vision/IR/UV-based sensing edge processing/distributed processing in the IoT camera fusion with other devices single-camera/multicamera/multidevice resilience application of smart vision in different domains Dr. Jose Manuel Menéndez García Guest Editor
Last updated by Jane Xu in 2021-04-25
Special Issue on Special Issue on Compressed Sensing for ECG Data Acquisition and Processing
Submission Date: 2021-07-31

Special Issue on Compressed Sensing for ECG Data Acquisition and Processing https://www.mdpi.com/journal/sensors/special_issues/compressed_sensing_ECG_data_acquisition_processing Dear Colleagues, Compressed sensing (CS) has recently been applied to ECG monitoring systems with the aim of either compressing the acquired data rate, reducing the noise, or even processing the ECG signal to discover anomalies. This Special Issue seeks innovative contributions on the application of recent CS results to the acquisition and processing of ECG signals, related but not restricted to the following topics: Signal acquisition schemes based on CS; Signal dictionaries and methods for dictionary optimization, learning, and adaptation; Reconstruction algorithms; Characterization and assessment of CS ECG monitoring systems; Hardware implementations of ECG monitoring systems based on CS; Analog-to-information converters for ECG monitoring; Processing of ECG samples acquired by CS; CS-based ECG signal denoising; Anomaly detection from compressed samples; CS-based heartrate and heartrate variation measurements; CS-based Internet of Things and Internet of Medical Things systems; Machine learning for CS; Energy-efficient CS systems; CS-based ECG segmentation and feature extraction. Guest Editors Prof. Dr. Luca De Vito Dr. Francesco Picariello Dr. Ioan Tudosa
Last updated by Silvia Li in 2021-04-25
Special Issue on Sensing for Robotics and Automation
Submission Date: 2021-07-31

https://www.mdpi.com/journal/sensors/special_issues/sra_Sensors Dear Colleagues, Robots use a large number of sensors to achieve good operation and control in automation production processes. With the drive toward “Industry 4.0,” the use of robotics and automation has become commonplace as they allow increased efficiency and precision. Therefore, the development of new sensors and measurement systems for robotics and automation requires new solutions that enable accurate, safe, and cost-effective operation. This Special Issue seeks to showcase reviews or rigorous original papers focused on remote sensing via UAVs (unmanned aerial vehicles); tactile sensing and sound sensors for robots; state of the art in automated tactile sensing; target tracking, including multiple targets with multiple sensors; visual sensing in robotics and automation; applications of robot sensing; multi-sensing automated systems; all new solutions of sensing systems for robotics and automation control of robotics. Potential topics include, but are not limited to, the following: Robotics Measurement system Mobile robotics Sensors UAV Inertial navigation systems Tracking control Automatic control Prof. Dr. Igor Korobiichuk Dr. Michał Nowicki Guest Editors
Last updated by Jane Xu in 2021-04-25
Special Issue on  Application of Motion Sensing Systems in Physical Activity and Sport
Submission Date: 2021-07-31

https://www.mdpi.com/journal/sensors/special_issues/amsspas_Sensors Dear Colleagues, The development of motion sensors enables the analysis of physiological, technical, and tactical behavior in physical activity and sport. The development and democratization of the use of sensors such as inertial motion units during the last decade have caused major changes in sport sciences as well as in health-related physical activity studies, which have undergone a great evolution as a consequence of motion analysis possibilities. At present, we can find a comprehensive use of sensors in physical-activity-related research: from sport medicine and rehabilitation to training and conditioning, health-related physical activity studies, physical education, and notational analysis. Moreover, motion sensors are common in our daily lives: current devices providing the analysis of our daily physical activity patterns have become very popular, enabling a new approach to daily exercise. From mobile phones to specific wearables (fitness trackers, sports watches, and smartwatches), the growing popularity of motion sensors provides the opportunity for self-monitoring physical activity behaviors for the whole population. In this Special Issue, we aim to face the challenges of the use of motion sensors in physical activity: - Studies on the basic development of motion sensors for physical activity and sport sciences; - Applied use of motion sensors in physical activity and sport sciences; - Studies on dealing with data access, data reduction and analysis; - Intelligent flows for collecting data from motion sensors and providing real-time physical activity and sport analysis; - The development and validation of quality standards in motion sensors in the physical activity and sport sciences; - The concurrent use of sensors (inertial motion units, eye and gaze tracking, biosignals, haptic feedback, etc.) in different physical activity and sport settings. This Special Issue is intended to become a comprehensive collection of useful state-of-the-art research studies. We will collect basic and applied research studies, tutorials, reviews, and position papers that address the use of motion sensors in physical activity and sport sciences. We will accept high-quality, original, unpublished papers that are not currently under review by any other journal or conference. Prof. Ernesto De La Cruz-Sánchez Prof. Dr. José Pino Ortega Dr. Sebastián Feu Guest Editors
Last updated by Jane Xu in 2021-04-25
Special Issue on special issue on EEG Signal Processing for Biomedical Applications
Submission Date: 2021-07-31

link: https://www.mdpi.com/journal/sensors/special_issues/EEG_Biomedical Special Issue Information Research focused on brain electrical signals derived from the electroencephalogram (EEG) is gaining traction among researchers from the biomedical, psychology, engineering, and computer science fields. EEG signals have great potential for use in biomedical applications for the diagnosis, treatment, and monitoring of conditions that can alter brain activity, such as mental fatigue. Applications for EEG signals have included the monitoring of brain diseases such as epilepsy, brain tumors, head and spinal injuries, and sleep disorders. Controlling the environment with our mind has always been a wish of humankind. Consequently, assistive technology applications using EEG signals such as brain–computer interfaces (BCI) have been the focus of substantial research, providing a platform for hands-free control. Measuring EEG is reliable, relatively cheap, portable, and non-invasive, making it a key methodology for affordable and effective research, as well as a promising clinical and healthcare tool. The aim of this Special Issue is to contribute to the current developments pertaining to using EEG signals for biomedical applications. We are inviting submissions of original research, as well as review articles, and new development reports in “Using EEG Signals for Biomedical Applications”. Topics of interest include (but are not limited to) the following: Biomedical applications using EEG signals; Assistive technologies using EEG; Brain–computer interfaces; EEG signal processing; EEG for monitoring; EEG as a biomarker; The influence of conditions such as fatigue on brain activity; EEG and sleep. Dr. Yvonne Tran (Centre for Healthcare Resilience and Implementation Science, Australian Institute of Health Innovation, Macquarie University) Guest Editor
Last updated by Vicky Cai in 2020-12-31
Special Issue on special issue on Indoor Positioning Technology for Monitoring Older Adults in E-Health Applications
Submission Date: 2021-07-31

link: https://www.mdpi.com/journal/sensors/special_issues/Indoor_Positioning_E-health Special Issue Information As a result of the rise in life expectancy, the world population is ageing, which is poised to become one of the most significant social transformations of the twenty-first century. For older adults, it is of great importance to maintain their independence and autonomy while remaining at their own homes. E-Health technology has proven to be a useful tool for remote monitoring and intervention to give care to older adults, while providing valuable tools to their caregivers and health practitioners to be aware of their current health status. Indoor positioning technologies (Wi-Fi, BLE, and sound/ultrasound) are able to provide positional information of older adults at home that can be used for continuous behavior monitoring for detecting potential health issues such as falls, cognitive decline, and adherence to medical prescriptions, to cite just a few. Machine learning algorithms are well suited for creating such models to tackle the high uncertainty and variability in the data used to model older adults’ behavior. The aim of this Special Issue is to contribute to the state-of-the-art research concerning indoor positioning technologies for monitoring older adults in E-Health applications. Keywords: E-Health; gerontechnology; indoor positioning; machine learning; remote monitoring; behavior modelling; continuous monitoring Dr. Óscar Belmonte Fernández (Computer Languages and Systems Department, Jaume I University) Guest Editor
Last updated by Vicky Cai in 2020-12-31
Special Issue on special issue on Edge Computing Architectures in Industry 4.0
Submission Date: 2021-07-31

link: https://www.mdpi.com/journal/sensors/special_issues/edge_computing_industry Special Issue Information It will soon be ten years since the term Industry 4.0 was first mentioned at the Hannover Fair in 2011. The fourth industrial revolution brings with it an ecosystem of enabling technologies such as cyberphysical systems, robotics, cybersecurity, big data analytics, Artificial Intelligence and predictive maintenance, additive manufacturing, and of course, the Industrial Internet of Things. Thanks to IIoT devices and platforms, all the elements involved in production processes are connected to each other and to the cloud, where they are represented by their digital twins. This makes it possible to characterize the different production processes in the industry’s value chain, extract value-added knowledge, and apply Big Data Analytics techniques in the cloud, including predictive and prescriptive maintenance, as well as detection of anomalous patterns using machine learning techniques. However, various challenges and limitations arise when sending data to the cloud, such as the high energy consumption of IoT devices or the challenges regarding the security and privacy of the data transferred. Furthermore, cloud service providers charge their costs according to the amount of data that are transferred, processed and stored in the cloud. Finally, in an architecture based solely on an IoT layer and a cloud layer, services may be interrupted if communication with the cloud is cut off. In this sense, Edge Computing architectures allow pre-processing and filtering of the data being transferred to the cloud, reducing costs, avoiding security problems, and allowing machine learning models to be run at the edge of the network with lower latency and higher service availability. For this purpose, this Special Issue will be focused on but not limited to the following topics: Innovative edge computing architectures; Industrial Internet of Things and edge computing; Machine learning at the edge in Industry 4.0 scenarios; Edge computing and cyber-physical systems; Internet of Robotic Things and edge computing; Management of additive manufacturing at the edge; Integration of operational technology in edge computing architectures; Innovative frameworks for managing data security and privacy at the edge; Novel applications of edge computing and IoT in Industry 4.0 scenarios: heavy and light industry, agro-industry, smart energy, healthcare, smart transportation, smart farming, smart logistics, etc. Keywords Internet of Things edge computing Industry 4.0 cyber-physical systems machine learning Dr. Ricardo S. Alonso (BISITE Research Group, University of Salamanca) Dr. Óscar García (BISITE Research Group, University of Salamanca) Dr. Miguel A. Sánchez Vidales (International University of La Rioja) Guest Editors
Last updated by Vicky Cai in 2020-12-31
Special Issue on  Wearable Sensors for Physical Activity Monitoring and Motion Control
Submission Date: 2021-07-31

https://www.mdpi.com/journal/sensors/special_issues/WSPAMMC Nowadays, there is a mass usage of wearable devices mainly focusing on promoting the healthy lifestyles of users. For example, bracelets and smartwatches have become commercial products well known and sold all over the world. Beyond the use of such devices for monitoring daily exercise, fitness levels and sport activities (sport performance), the last decade has shown an increasing interest in the development of mobile and wearable technologies for health promotion in many different ways. Physical activity monitoring and motion control through wearable technology provide valuable information for rehabilitation purposes, physical and even cognitive assistance. In addition, advances in artificial intelligence and machine learning make it possible to process acquired data from wearable sensors/devices, for instance, to detect postural problems in everyday physical activities (work and home ergonomics), to predict functional decline (early diagnosis and prevention), to identify the risk of falls in elders or, more specifically, to segment, classify and recognize human motion for gait analysis purposes, among others. This Special Issue is interested in all types of wearable sensors and mobile technologies dedicated to physical activity monitoring and motion control in the domains of healthcare, industry, home, sport, and more. Dr. Jesús Fontecha Dr. Iván González Guest Editors
Last updated by Daisy Wang in 2020-12-31
Special Issue on RFID and Zero-Power Backscatter Sensors
Submission Date: 2021-07-31

https://www.mdpi.com/journal/sensors/special_issues/RZPBS The growth of Internet of Things (IoT) applications requires energy efficient sensors that are capable of working autonomously, have reduced environmental pollution associated with battery waste, have improved lifespans, and have reduced manual recharge problems. Green sensors based on radio frequency identification (RFID), where the communication between the reader and the tag is based on backscattering communications, is an example of IoT technology. The integration of sensors in passive and semi-passive tags to monitor different magnitudes at different frequency-bands and applications has experienced a growing commercial interest. Different approaches, such as chip-based and chipless sensors, have been investigated. Recently, there has been increasing market interest in battery-less sensors based on near-field communication (NFC), which incorporates energy harvesting systems, and ultra high frequency (UHF) RFID. Moreover, the advances in communication technologies at millimeter-wave frequency bands have opened new opportunities for RFID and radar sensor applications. In addition to RFID technology, backscatter radio is a promising communication scheme for novel long-range communications based on zero-power backscatters that allow for communication by ambient backscattering radio-frequency signals. This Special Issue is focused on sensors based on RFID and backscattering communication systems. Potential topics include but are not limited to the following: Zero-power wireless sensors and ambient backscatter communications Chipless sensors Near-field communication (NFC) sensors UHF RFID sensors Wearable and implanted devices based on backscatter communication Millimeter-wave backscatter sensors UWB sensors Backscatter sensors with energy harvesting Prof. Dr. Antonio Lázaro Prof. Dr. David Girbau Prof. Dr. Ramon Villarino Guest Editors
Last updated by Daisy Wang in 2020-12-31
Special Issue on Sensor Data Fusion and Analysis for Automation Systems
Submission Date: 2021-08-15

Dear Colleagues, The MDPI Journal of Sensors (ISSN 1424-8220, IF 3.275) currently running a Special Issue entitled "Sensor Data Fusion and Analysis for Automation Systems” which is open for submissions until 15 August 2021. https://www.mdpi.com/journal/sensors/special_issues/SensorDataFusion_Analysis_AutomationSystems This Special Issue is devoted to new advances and research results on sensor data fusion and analysis for various automation systems in transportation, robotics, agriculture, and industry. It will publish work exploring frontier technology and applications in related fields. The topics of interest for this issue include, but are not limited to the following: Multi-sensor fusion and feature representation Information acquisition and analysis for automation Sensor signal processing and data analysis Big data mining for automation Data fusion based on monitoring for automation Artificial intelligence for automation systems Intelligent robotics and machine vision Machine learning based on prediction and decision making Intelligent control for automation systems Should you have any questions, please feel free to contact Rain.liu@mdpi.com.
Last updated by Rain Liu in 2020-12-30
Special Issue on Applications of Internet of Things Networks in 5G and Beyond
Submission Date: 2021-08-15

Dear Colleagues, The pervasiveness of Internet of Things technology is expected to be ever-increasing in the next decade, with applications including healthcare, smart manufacturing, transport and logistics, and security, to name but a few. This explosion of devices, with different application scenarios, requires new networking paradigms and is heavily influencing the new communications standards like 5G – where the most relevant differences with respect to the previous generation are, indeed, in the support for IoT-based applications. Even though 5G can, and will be, an enabling technology, there is still a wide area of research, both theoretical and applicated, that has to be performed. Examples of research topics under active development are spectrum coexistence, resource allocation, remote area connectivity, heterogeneous network integration, network optimization, etc. The research, of course, is not limited to improvements in 5G and intends to pave the way toward future standards like 6G. The challenges and opportunities are not limited to communication technologies. As a matter of fact, IoT systems will produce a massive amount of data that will require proper and timely processing. In this context, the research will need to tackle issues arising from the privacy and security of user data, big data processing, networking paradigms based on virtualization, and network and resource slicing, among others. A further set of challenges will be driven by the need for new paradigms to cope with cyber threats, as IoT systems are tightly coupled to the cyber-physical domain, meaning that threats to the cyber domain can potentially have severe outcomes in the physical domain. Finally, the importance of green networking and computing paradigms are expected to increase in the future, both because IoT devices are typically mobile and because energy consumption reduction is nowadays a priority. This Special Issue seeks innovative works on a wide range of research topics, spanning both theoretical and systems research, including results from industry and academic/industrial collaborations, related but not restricted to the following topics: Machine learning/AI applications for 5G networks Distributed and federated machine learning/AI applications to 5G and IoT domains 5G and IoT systems integration Security and privacy aspects of 5G and IoT pervasive networks 5G and IoT heterogeneous networks 5G and IoT use cases and scenarios (e.g., e-health, vehicular networks, transport systems, autonomous driving, logistic management, etc.) Age of information in pervasive networks Network virtualization systems for 5G and IoT networks (e.g., SDN, NFV, virtual machine placement and migration, network slicing, etc.) Service and network planning for IoT and 5G systems Edge networking and computation for 5G/IoT domains Evolution of 5G and IoT toward 6G and beyond networks Full duplex communications in 5G and IoT networks
Last updated by Chloe Guo in 2021-04-25
Special Issue on Applications of Internet of Things Networks in 5G and Beyond
Submission Date: 2021-08-15

https://www.mdpi.com/journal/sensors/special_issues/IoT_Beyond Dear Colleagues, The pervasiveness of Internet of Things technology is expected to be ever-increasing in the next decade, with applications including healthcare, smart manufacturing, transport and logistics, and security, to name but a few. This explosion of devices, with different application scenarios, requires new networking paradigms and is heavily influencing the new communications standards like 5G – where the most relevant differences with respect to the previous generation are, indeed, in the support for IoT-based applications. Even though 5G can, and will be, an enabling technology, there is still a wide area of research, both theoretical and applicated, that has to be performed. Examples of research topics under active development are spectrum coexistence, resource allocation, remote area connectivity, heterogeneous network integration, network optimization, etc. The research, of course, is not limited to improvements in 5G and intends to pave the way toward future standards like 6G. The challenges and opportunities are not limited to communication technologies. As a matter of fact, IoT systems will produce a massive amount of data that will require proper and timely processing. In this context, the research will need to tackle issues arising from the privacy and security of user data, big data processing, networking paradigms based on virtualization, and network and resource slicing, among others. A further set of challenges will be driven by the need for new paradigms to cope with cyber threats, as IoT systems are tightly coupled to the cyber-physical domain, meaning that threats to the cyber domain can potentially have severe outcomes in the physical domain. Finally, the importance of green networking and computing paradigms are expected to increase in the future, both because IoT devices are typically mobile and because energy consumption reduction is nowadays a priority. This Special Issue seeks innovative works on a wide range of research topics, spanning both theoretical and systems research, including results from industry and academic/industrial collaborations, related but not restricted to the following topics: Machine learning/AI applications for 5G networks Distributed and federated machine learning/AI applications to 5G and IoT domains 5G and IoT systems integration Security and privacy aspects of 5G and IoT pervasive networks 5G and IoT heterogeneous networks 5G and IoT use cases and scenarios (e.g., e-health, vehicular networks, transport systems, autonomous driving, logistic management, etc.) Age of information in pervasive networks Network virtualization systems for 5G and IoT networks (e.g., SDN, NFV, virtual machine placement and migration, network slicing, etc.) Service and network planning for IoT and 5G systems Edge networking and computation for 5G/IoT domains Evolution of 5G and IoT toward 6G and beyond networks Full duplex communications in 5G and IoT networks Prof. Dr. Tommaso Pecorella Dr. Benedetta Picano Guest Editors
Last updated by Chloe Guo in 2021-04-25
Special Issue on Special Issue on Microgenerators Applicable in the MEMS/NEMS Sensors
Submission Date: 2021-08-31

Special Issue on Microgenerators Applicable in the MEMS/NEMS Sensors https://www.mdpi.com/journal/sensors/special_issues/microgenerators_applicable_mems_nems_sensors Dear Colleagues, The aim of the selected publications is to describe both theoretical approaches to and principles of harvesting, such as the conversion of different "residual" forms of energy into electrical energy with the required parameters and measurable transformation efficiency, as well as a number of different approaches to extracting potential and dynamic forms of local system energy. Areas of interest are mainly: Theoretical foundations of the principles of extraction/transformation (electromagnetic field) as well as equipment for the conversion of any form of energy into electrical energy with a wider application potential, for structures of millimeter, micrometer or nanometer technology, power supply for sensing technology, supporting electronics, etc. Some specific applications (in the areas of both technology and manufacturing issues, as well as tasks related to implementation) in MEMS and NEMS sensors. The appropriate selection of the principles of harvesting (efficiency, performance, limiting factors of activity, multidisciplinary use, interdisciplinary solutions, special applications of material, medical, space, microscopic and other technologies) for the selected shape, application and size of the sensor. Prof. Dr. Pavel Fiala Guest Editor
Last updated by Silvia Li in 2021-04-25
Special Issue on Special Issue on Fusion of Multi-Sensors for Underwater Navigation and Localization
Submission Date: 2021-08-31

Special Issue on Fusion of Multi-Sensors for Underwater Navigation and Localization https://www.mdpi.com/journal/sensors/special_issues/underwater_navigation_localization Dear Colleagues, Advances in underwater robotics and autonomous systems have led to the emergence of underwater autonomous vehicles (AUVs) for applications ranging from undersea surveillance through seafloor mapping and seabed characterization to seabed survey and object recognition. At the same time, the scientific community has been deploying unattended systems and sensors at the seafloor or drifting in the water column at increasing depths and for increasing durations. In all these applications, key enabling technologies are navigation and localization. In the former, the vehicle is set to keep track on its planned course and to link findings to a geographic location. In the latter, an accurate estimation of the sensor’s location is required not only to confirm the location of the planned deployment, but also to connect findings to the geographic location. In the absence of GPS readings underwater, the deployed system relies on its onboard sensors and on external information for navigation. Navigation of submerged vehicles is a demanding process with unique challenges, such as the effect of the water current, handling noise sources with few to no reliable measurements, and modeling dynamics in an ever-changing environment. Different than terrestrial or aerial navigation, where navigation fixes can be obtained from sources such as GPS or external beacons, handling the drift of underwater navigation system calls for the fusion of multiple sensors. These can be self-measurements from inertial sensors, depth meters or sonar systems, or external information from acoustic beacons, bathymetric maps, or objects of opportunity found on the seabed. Such fusion holds the potential to mitigate measurement noise, improve convergence, and resolve position ambiguities. Recent years have shown innovative work both in improving the accuracy of navigation sensors and in the analysis to evaluate the navigation performance. Both experimental and theoretical works have constantly improved navigation capabilities, allowing AUVs to remain longer and search farther underwater. It is now the time to push these limits further by developing new ambitious methods for multisensor navigation. This Special Issue seeks innovative works in a wide range of research topics, spanning both theoretical and systems research, including results from industry and academic/industrial collaborations, related but not restricted to the following topics: Algorithms to combine sensors for underwater navigation or localization; Design of underwater navigation or localization systems combining multiple sensors; Filtering techniques for multisensor fusion; Experimental results demonstrating advantages of multisensor navigation or localization; Analysis of navigation and localization bounds, and limitation for the use of multisensors; Relative navigation in structured underwater environments; Cooperative localization and navigation. Guest Editors Dr. Roee Diamant Dr. Nuno Cruz
Last updated by Silvia Li in 2021-04-25
Special Issue on Advanced Systems for Human Machine Interactions
Submission Date: 2021-08-31

Advanced Systems for Human Machine Interactions https://www.mdpi.com/journal/sensors/special_issues/systems_human_machine_interactions Dear Colleagues, Machines have been an important part of human life since the first industrial revolution. Recently, however, they have become a part of our lives in way that could hardly be imagined even a couple of decades ago. Concepts such as the Internet of Things, Artificial Intelligence, Machine Vision, 5G networks, etc. are pointing toward a future where machines and humans will become even more connected. A very important part of this process are human–machine interface (HMI) systems. As they are the part the human most often comes in contact with when dealing with machines, their design is very important and can often make the difference between certain applications being accepted among users or not. In this Special Issue titled “Advanced Systems for Human–Machine Interactions”, we aim to provide a collection of papers that present the latest research in all areas of human–machine interactions for various applications. The Special Issue solicits submissions from scientists and engineers, whose work represents a novel contribution to the field of HMI. The articles that this issue is looking for must be original work or comprehensive reviews, which should not be published or submitted for publication to any other journal. Topics of interest include but are not limited to the following: Machine vision; Artificial intelligence; Advanced sensorial systems; Physiological sensing; Collaborative robotics. Guest Editor Prof. Primož Podržaj
Last updated by Silvia Li in 2021-04-25
Special Issue on Computer-Aided and Game-Based Telerehabilitation and Telemonitoring Platforms
Submission Date: 2021-08-31

Dear Colleagues, Telerehabilitation has long been recognized as a necessary part of the neurorehab process. With the added pressure due to the COVID pandemic, there is more reason to develop cost-effective systems for safe neurorehab programs that can be done remotely (i.e., in-home or in rural communities) and, importantly, monitored by clinician specialists (telemonitoring). Regular clinical-support of home and rural programs with protocols that can be easily updated will help create better-targeted and personalized solutions for patients and achieve the desired training effect. In addition to increasing accessibility, there is a need to improve compliance of exercise regimes over the entire population, ranging from children to elderly patients. An emerging approach to engage patients in therapy is to incorporate computer games in which a range of learning elements with interactive motor and cognitive challenges help individuals to participate in motor activities and the practice of repetitive tasks. The collection will highlight the range of technologies (sensors, digital media, intelligent agents) used and emerging best practices regarding their specifications, acceptability/usability, engagement and therapeutic effects. Prof. Dr. Tony Szturm Prof. Dr. Nariman Sepehri Dr. Sanjay T. Parmar Guest Editors
Last updated by Chloe Guo in 2021-04-26
Special Issue on Structural Health Monitoring and Non-Destructive Testing for Engineering Applications: Advances in Sensor and Technologies
Submission Date: 2021-08-31

https://www.mdpi.com/journal/sensors/special_issues/shmntea_sensors Dear Colleagues, Non-destructive testing (NDT) and structural health monitoring (SHM) are strategic procedures for the non-invasive assessment of the health state of materials and structures. Several NDT protocols guarantee that each engineering component enters in service after satisfying a series of stringent tests ensuring the maximum safety level for both persons and products. New studies in this field have a strategic and essential role in order to reduce the NDT costs and improve test performance. As a natural evolution of NDT procedures, structural health monitoring (SHM) has been developing fast, to reduce maintenance costs and limit design constraints. Continuous monitoring of both components and their assemblies ensures high levels of safety, reducing the number of inspections as well. This Special Issue focuses on fostering technical improvements and new technologies developing for characterization and real-time monitoring of mechanical parts and, generally, structures in a variety of engineering fields (automotive, nuclear, petrochemical, archeology, cultural heritage, aerospace, and so on). We would like to invite original research articles as well as review articles that contain theoretical, analytical, and experimental investigations covering all aspects of NDT&E and SHM. Keywords Sensors and transducers for NDT/SHM Advanced techniques for NDT/SHM measurements Smart sensors for NDT/SHM Methods and systems for designing, optimizing, and characterizing NDT instruments and devices Data processing and advanced techniques for NDT and SHM measurements Reliability of NDT/SHM New SHM methodologies and damage assessment criteria Methods and devices to optimize the performance of existing NDT techniques Artificial intelligence in the data analysis and damage prediction applied to NDT/SHM Dr. Leandro Maio Dr. Vittorio Memmolo Dr. Marco Laracca Guest Editors
Last updated by Jane Xu in 2021-04-27
Special Issue on Artificial Intelligence for Network of UAVs and Swarms of Small Satellites
Submission Date: 2021-08-31

https://www.mdpi.com/journal/sensors/special_issues/sss_sensors Dear Colleagues, The use of aerial drones, also known as unmanned aerial vehicles (UAVs), has proven to be very useful in rescue and monitoring operations, and more particularly, in ensuring population surveillance during the management of the COVID-19 pandemic. Drones can be used for communication, monitoring and delivery. Deep space exploration requires developing and deploying new generations of flexible and resilient swarms of small satellites, with adaptive capabilities and intelligent functions. The integration of unmanned vehicles with terrestrial and space networks is under standardization and experimentation. Research in this domain revealed several critical issues, such as autonomous deployment, navigation and control, energy management and seamless services, over heterogenous networks. Advanced methods should be designed for the reliable and efficient functioning of the network of unmanned vehicles, and swarms of small satellites. This Special Issue is looking for contributions investigating the use of Artificial Intelligence in the field of placement, smart network control and navigation of unmanned vehicles and swarms of small satellites from theoretical to experimental studies. Potential topics include but are not limited to the following: Efficient and resilient smart deployment of aerial drones; Smart deployment and control of swarms of small satellites; Smart control of unmanned vehicles aided networks; UAV aided mobile sensor networks; Autonomous vehicles networks monitoring; Energy efficient UAV tracking of mobile targets; Energy harvesting for UAV networks; Traffic monitoring aided by unmanned vehicles; Intelligent resource allocation schemes for UAV and Swarms of nano-satellite networks; Beyond 5G Space-Air-Ground networks control; Coverage optimization and control in UAV surveillance; Collision avoidance for unmanned vehicles; Autonomous networks for deep space exploration; AI-based control of UAV and Swarms of nano-satellite networks; Experimental platforms for UAV networks, UAVs aided mobile networks and Swarms of small satellites Keywords AI UAVs small satellites smart placement network control navigation Dr. Maria Rita Palattella Prof. Dr. Riadh Dhaou Guest Editors
Last updated by Jane Xu in 2021-04-27
Special Issue on  Toward the Application of Smart Self-Sensing Nanocomposites to Structural Health Monitoring
Submission Date: 2021-08-31

https://www.mdpi.com/journal/sensors/special_issues/SSNSHM The multifunctional properties of epoxy-based nanocomposites reinforced with carbon nanoparticles are attracting the attention of scientists and designers of structural and prognostic health monitoring systems. The idea of creating a composite structure capable of self-sensing potential deterioration mechanisms within the material by a measure of its piezoresistivity could potentially revolutionize the concept of sensor network design. However, one main factor limits the move toward the industrial application of this technology: the lack of self-sensing robustness hampers the predictability of the sensor performance in terms of sensitivity to the presence of damage and the capability to track its trend during the course of its evolution. This Special Issue is intended to bring together the various efforts made in developing methods to increase the readiness of this technology for future industrial application, including manufacturing strategies, modeling frameworks, and the development of ternary-state nanocomposites, with a special focus on increasing the sensor performance predictability. Dr. Claudio Sbarufatti Prof. Dr. Alberto Jiménez Suárez Guest Editors
Last updated by Daisy Wang in 2020-12-31
Special Issue on Drone Sensing and Imaging for Environment Monitoring
Submission Date: 2021-09-15

Dear Colleagues, The development and diffusion of unmanned and remote controlled flying platforms (drones) has induced the universities and scientists to use these systems in many scientific field where is fondamental the observation, the inspection and management of critical areas by the remote sensing. A drone can be equipped with small and compact instrumentation, precision GPS systems, thermal and multispectral cameras, magnetometers and high resolution cameras capable of performing reporting maps in very high precision, thermal photographs, high definition video footage, but also gas or ground material sampling or tools release. Thus allowing to explore extreme sites and collect a wide range of useful data and details in short time for the study of natural phenomena and environmental monitoring, with very low operating costs. These high-performance multipurpose flight systems can now safely access inaccessible environments. At the same time, they have stimulated technological research to develop new airborne instruments and sensors and new remote observation techniques. This Special Issue is dedicated to drone sensing and applications of sensors and tools designed for environmental monitoring to be integrated on board drones" with a new sentence "This special issue is dedicated to environmental detection through drones and the application of new sensors and tools designed to be integrated on board drones and used for environmental research and monitoring https://www.mdpi.com/journal/sensors/special_issues/drone_sensing_imaging Keywords remote sensing infrared camera remote sampling multipurpose drone instruments release gas sensors multispectral camera Dr. Giuseppe Di Stefano Guest Editor
Last updated by James Su in 2021-04-26
Special Issue on special issue on Well-Being, Comfort and Health Monitoring through Wearable Sensors
Submission Date: 2021-09-20

link: https://www.mdpi.com/journal/sensors/special_issues/Health_Wearable_Sensors Special Issue Information The development of wearable technologies over the past years has opened up the possibility of extracting physiological parameters just through using low cost and non-invasive systems. Continuous monitoring of physiological and personal parameters, e.g., electrocardiograms, electrodermal activity, electroencephalograms, skin temperature, activity level, etc., through wearable sensors has been demonstrated to define the user's well-being, comfort, and health status in the life environments, both indoor and outdoor. In this Special Issue, we call for papers presenting innovative solutions and signal processing techniques to measure the well-being, comfort, and health status of the user in the life environments, i.e., indoor and outdoor, through wearable sensors eventually integrated in sensor networks. The papers have to consider the accuracy in the measurement of such quantities. Keywords wearable sensors well-being, health comfort measurements accuracy life environment Dr. Gian Marco Revel (Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche) Dr. Sara Casaccia (Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche) Guest Editors
Last updated by Vicky Cai in 2020-12-31
Special Issue on ccurate Synchronization in IoT
Submission Date: 2021-09-30

Special Issue "Accurate Synchronization in IoT" website: https://www.mdpi.com/journal/sensors/special_issues/ASIoT Deadline for manuscript submissions: 30 September 2021 Dear Colleagues, Internet of Things (IoT) combined with Wireless Sensor Networks (WSN) have experienced a great evolution in the last decade, opening the door to new and enhanced applications that in some scenarios can require high accurate synchronization, such as real time monitoring, ranging, collaborative beamforming, etc. Notice that these networks are set up with small distributed nodes, based on low cost components, that have limited power supply, processing, memory and communications. Due to their poor performance and quality of their clocks, usually time synchronization is in the order of milliseconds and a higher precision is a great challenge. However, using advanced synchronization protocols, emergent communication technologies, such as Ultra Wide Band (UWB), and/or tuning slightly these nodes, we can achieve this time accuracy. This Special Issue on “Accurate synchronization in IoT" aims to gather all these recent developments and advances to share with the research community. Submissions are expected to focus on both theoretical and practical aspects and applications. New ideas proposing disruptive approaches are also welcome. Topics of interest include but are not limited to the following areas: Ultra-wideband communications; Network timing; Synchronization protocols; Modulations and symbol correlation; IEEE 802.15.4 transceivers; Open-source solutions. Dr. Juan J. Perez-Solano Dr. Santiago Felici-Castell Guest Editors
Last updated by Callie Liu in 2020-12-30
Special Issue on Integrating the Internet of Things and Blockchain-Enabled Applications: Current Practices, Opportunities and Challenges
Submission Date: 2021-09-30

website: https://www.mdpi.com/journal/sensors/special_issues/IIoTBEA Dear Colleagues, The Internet of Things (IoT) applications and blockchain technology are driving Industry 4.0, and their integration seems almost mandatory for the years to come. Various weaknesses of IoT-related applications such as security vulnerabilities, data privacy and confidentiality issues could be tackled by the non-repudiable and forensics-by-design nature of blockchain technology. Arguably, blockchain-enabled applications could serve as a trusted environment for intra- and intersystem IoT communications and foster the development of fine-grained access control mechanisms of IoT data and services. Other benefits of integrating blockchain and IoT applications, particularly through smart contracts, include data integrity, forensics and chain-of-custody for IoT devices and sound identity management schemes. Integrating, however, IoT sensors and blockchain-enabled applications might be a daunting task, especially when considering that such integration should occur within current enterprise resource planning (ERP) or cloud-based systems widely applied in all domains of global business and industry. The advent of 5G technologies also creates new challenges for successfully integrating IoT and blockchain. In particular, 5G-enabled IoT applications call for high data rates, network scalability and a massive number of device connectivity, technical requirements that challenge current blockchain platforms’ scalability features. Additionally, lack of interoperability and standardization heavily affect blockchain platforms’ potential to be fully integrated with IoT-related applications. In this Special Issue of Sensors, we invite submissions focusing on the symbiotic relationship and integration potential of IoT-related applications and blockchain technology. We welcome submissions that offer important technical, conceptual and empirical insights into how IoT and blockchain could be successfully integrated within current ERP or cloud-based systems, particularly by tackling the various technical, security, operational and regulatory issues prevalent in today’s business context. Of particular interest are papers focusing on integrating blockchain and IoT in specific sectors such as industrial manufacturing, logistics, finance, health, energy, etc. Dr. Thomas K. Dasaklis Dr. Fran Casino Dr. Rachaniotis Nikolaos Guest Editors
Last updated by Callie Liu in 2020-12-30
Special Issue on special issue on Portable Sensor Systems for Microbial Application
Submission Date: 2021-09-30

link: https://www.mdpi.com/journal/sensors/special_issues/Portable_Sensor_Microbial Special Issue Information Bacterial contamination is routinely screened in different areas of application, such as food production and processing, environmental monitoring, cosmetics production, and industrial and military applications. The measurement of microbial concentration is important since high microbial contamination or the presence of pathogens can seriously endanger consumer health. It is usually carried out by laboratory analysis, and this results in high costs for analysis and long response times. Recently, much research has been carried out to propose novel techniques for microbial analysis that can allow low-cost and in situ measurements outside a laboratory environment. Such techniques are based on different transduction principles, such as electrical impedance spectroscopy (EIS), amperometry, voltammetry, near infrared (NIR) optical analysis, piezoelectricity, and fluorescence. One important characteristic of the proposed techniques is potential implementation in the form of an embedded portable electronic system, based on a microcontroller or FPGA, to allow microbial analysis outside a laboratory to also be performed by nonskilled personnel. Moreover, the recent wide diffusion of smartphones with a high processing capability that integrate wireless communication systems and a rich sensor set offers an optimal platform to design low-cost mobile sensing systems. The editors welcome the submission of high-quality research papers not previously published in other journals as well as review articles discussing recent advancements in the development of portable sensor systems for microbial analysis and innovative techniques for microbial analysis that can be easily implemented in the form of an electronic embedded system. Keywords Sensor Bacteria Microbial analysis Portable system Biosensor Lab-on-a-chip Dr. Marco Grossi (Dipartimento di Ingegneria dell'Energia Elettrica e dell'Informazione "Guglielmo Marconi") Guest Editor
Last updated by Vicky Cai in 2020-12-31
Special Issue on Sensors and AI for Movement Analysis
Submission Date: 2021-09-30

https://www.mdpi.com/journal/sensors/special_issues/SAMA Dear colleagues, Movement analysis is currently one of the more attractive research fields and covers several applications from clinics to sports, as well as robotics and industry. In recent decades, the introduction of sensor-based systems to quantitatively perform movement analyses represented a breaking point among researchers, allowing them to overcome the limitations associated with the previous subjective methodologies. The most widespread sensors are optoelectronic systems, force platforms, inertial sensors, physiological sensors, probes for electromyography, and others, which permit one to fully understand the mechanism related to different motor tasks. In recent years, artificial intelligence has been introduced in movement analysis as a further tool to provide useful information with an automatic approach, also thanks to the increasing availability of large open datasets obtained through quantitative human motion analysis. It is clear that constant technological improvements have led to an ever-increasing number of possible innovative studies in this field. Thus, this Special Issue aims to promote innovative studies based on the application of sensors and AI for movement analysis in several fields, such as clinics, sports, robotics, and industry; the implementation of innovative methodologies for data analysis; the design of innovative sensors; and the publication of open databases for motion analysis. Keywords movement analysis wearable sensors artificial intelligence experimental biomechanics kinematics kinetics posturography muscle activities sensor-based system Prof. Dr. Stefano Rossi Guest Editor
Last updated by Jane Xu in 2021-04-27
Special Issue on Automatic Detection of Seismic Signals
Submission Date: 2021-09-30

https://www.mdpi.com/journal/sensors/special_issues/adss_sensors Dear Colleagues, Automatic detection and picking of seismic signals is crucial for seismic networks, which continuously monitor and work with huge volumes of data. In this situation, manual picking is tedious work in which some small events can go unnoticed and others can produce false alarms. Accordingly, automatic picking algorithms are in constant development. New methodologies based on energy analysis, artificial neural networks, maximum likelihood methods, fuzzy logic theory, polarization analysis, hidden Markov models, autoregressive techniques, higher order statistics, wavelet transform, or template matching, among others, are continuously being investigated. Accurate and reliable identification and detection of seismic phases is essential for subsequent real-time analysis. The information contained in the different seismic phases allows the expected magnitude, the epicentral location of an event, and other parameters that might be used by earthquake early-warning systems to be estimated. The aim of this Special Issue is to present the most recent advances in the automatic detection and phase picking of seismic signals. Topics related to this Special Issue of Sensors include, but are not limited to: Automatic seismic event detection; Accurate seismic phase picking; Real-time processing of seismic signals; New methodologies for the automatic estimation of earthquake parameters; Monitoring and early-warning systems. Dr. Sergio Molina Dr. Juan Jose Galiana-Merino Guest Editors
Last updated by Jane Xu in 2021-04-27
Special Issue on Machine Learning and Signal Processing in Sensing and Sensor Applications
Submission Date: 2021-09-30

https://www.mdpi.com/journal/sensors/special_issues/mlsspas_sensors Dear Colleagues, In recent decades, machine learning (ML) technologies have made it possible to collect, analyze, and interpret a large amount of sensory information. As a result, a new era of intelligent sensors is emerging that changes the ways of perceiving and understanding the world. The integration of ML algorithms with artificial intelligence (AI) technology benefits other areas such as Industry 4.0, Internet of Things, etc. leveraging these two technologies, it is possible to design sensors tailored to specific applications. To this end, signal data, such as electrical signals, vibrations, sounds, accelerometer signals, as well as any other kind of sensory data like images, numerical data, etc. need to be analyzed and processed from real-time algorithms to mine useful insights and to embed these algorithms in sensors. This Special Issue calls for innovative work that explores new frontiers and challenges in the field of applying ML/AI technologies and algorithms for high-sample-rate sensors. It includes new ML and AI models, hybrid systems, as well as case studies or reviews of the state-of-the-art. The topics of interest include, but are not limited to the following: ML algorithms in smart sensor systems AI models in smart sensor systems ML/AI‐enabled smart sensor systems Practical smart-sensor applications Practical smart-sensing systems Health and disease data management Medical image diagnosis and analysis Biology data analysis Smart visual imaging sensing systems Object detection and recognition Smart-sensors for environmental pollution management Smart-sensors for precision agriculture and food science Big data analytics for sensor data Intelligent real-time algorithms for sensor data Features for signal classification Feature discovery Applications of AI and ML in sensor domains: energy, IoT, Industry 4.0, etc. Dr. Gianni D’Angelo Guest Editor
Last updated by Jane Xu in 2021-04-27
Special Issue on  Optical Spectral Sensing and Imaging Technology
Submission Date: 2021-09-30

https://www.mdpi.com/journal/sensors/special_issues/OPSIT In optical spectral sensing and imaging technologies, spatial information is combined with spectroscopy. These methods offer fast and non-destructive methods which have evolved into powerful analysis tools for science and industry. In recent years, the related areas have developed rapidly. On the one hand, development is being driven forward both technically and methodically. Camera/imaging technology is developing very quickly—especially, the first hyperspectral chips have become commercially affordable. Additionally, their use in smartphones as sensors will not be long in coming. Another driving force is the ever more powerful computers and programs that enable us to visualize and analyze the enormous amounts of data in a reasonable amount of time using chemometric methods or AI applications. This Special Issue will focus on (i) current state-of-the-art of optical sensors for spectral sensing and imaging, (ii) recent technological improvements in new devices/sensors, (iii) mathematical methods for data analysis, and (iv) scientific/industrial applications. Both original research papers and review articles describing the current state-of-the-art in this research field are welcome. The Editor intends with this SI to provide an overview of the present status as well as a future perspective of these topics. The manuscripts should cover, but are not limited to, the following topics: Existing methodology and instrumentation; Emerging novel instrumentation and techniques; Spectral/data unmixing; Spectral variability; Classification, segmentation, and compression; Data fusion, information extraction, and simulation; Target detection; Hyperspectral image classification; High performance computing; AI applications and chemometric modeling; Calibration transfer; Scientific and industrial applications—all topics are welcome. Prof. Dr. Marc Brecht Department of Applied Chemistry, Hochschule Reutlingen, Alteburgstrasse 150, Reutlingen, Germany Guest Editor
Last updated by Daisy Wang in 2020-12-31
Special Issue on special issue on Advances in Spectroscopy and Spectral Imaging
Submission Date: 2021-10-01

link: https://www.mdpi.com/journal/sensors/special_issues/Spectroscopy_Spectral_Imaging Special Issue Information Spectroscopy aims at recovering the spectral signature of light at a scene point, within a given spectral range and a given spectral resolution. Spectral imaging enhances this functionality by adding spatial dimension, leading to a spatiospectral data representation (i.e., a spectral data cube). On one hand, novel hardware designs dedicated to spectroscopy and spectral imaging (SSI) are demanded to improve the efficiency, flexibility, or compactness of the SSI systems. On the other hand, dedicated data processing is required for the emergence of SSI systems. Recent advances in the field could potentially lead to the massification of SSI, and a better implication of SSI in applications, such as for computer vision, computer graphics, or remote sensing. To further help SSIs to break through into applications, it is necessary to go beyond our understanding of their limitations. This Special Issue focuses on these topics, so the different issues, achievements, and progress from different disciplines are available from one single issue. Potential topics include but are not limited to: Technology: spectral sensors, optical design, camera design, acquisition setup, etc. Computational algorithm: imaging model, data processing, noise reduction, calibration, image enhancement, demosaicing, super-resolution, high dynamic range, etc. Inverse problem: spectral reconstruction, illuminant estimation, reflection mode separation, rendering, matching, etc. Data mining for spectral information: learning, CNN, time series, etc. Applications in computer vision: medical imaging, automotive, cultural heritage (classification, text analysis), etc. Applications in computer graphics: cultural heritage (visual reproduction), etc. Other SSI applications in remote sensing, chemistry, biology, etc. Keywords spectral sensors spectroscopy spectral imaging multispectral imaging hyperspectral imaging spectropolarimetric imaging Dr. Pierre-Jean Lapray (Université de Haute-Alsace) Dr. Jean-Baptiste Thomas (The Norwegian Colour and Visual Computing Laboratory, Norwegian University of Science and Technology) Dr. Yusuke Monno (Okutomi & Tanaka Laboratory, Department of Systems and Control Engineering, School of Engineering, Tokyo Institute of Technology) Guest Editors
Last updated by Vicky Cai in 2020-12-31
Special Issue on Multiple Access Techniques in Emerging Wireless Systems: Performance, Applications and Challenges
Submission Date: 2021-10-15

website: https://www.mdpi.com/journal/sensors/special_issues/multiple_access_techniques Dear Colleagues, With the expected increase of the number of users in 5G networks, techniques based on orthogonal multiple access (OMA) may no longer meet the new requirements, particularly in terms of high spectral efficiency, low latency, as well as massive connectivity of devices. In this context, the non-orthogonal multiple access (NOMA) technique is at the forefront, emerging as one of the most promising radio access techniques in next-generation wireless communications. It consists of serving multiple users using the same resource in terms of time, frequency, and space. Compared to OMA techniques, NOMA appears as a viable solution capable of enhancing spectrum efficiency, reducing latency with high reliability, and enabling massive connectivity of sensor nodes, IoT equipment, and other smart devices. Recent studies have shown some existing evidence of performance improvement when NOMA is integrated with effective wireless communication techniques such as multiple-input–multiple-output (MIMO), beamforming, cooperative communications, etc. However, this new technique introduces additional challenges that need to be solved, such as interference management due to superimposition on the same resource and security issues. This Special Issue focuses on research and development of NOMA-based systems. Researchers are invited to contribute high-quality articles on the latest advances related to improving and solving key challenges within NOMA-based systems, including emerging applications and algorithms to improve the overall performance. Both original practical work and review articles are welcome. Topics of interest include but are not limited to: Resource allocation in NOMA-based systems; Resource optimization in NOMA; NOMA in full-duplex wireless networks; Cooperative communication or relaying with NOMA; Emerging applications of NOMA; Performance analysis of NOMA systems; Simulation of NOMA systems; Hybrid NOMA; Privacy and security issues in NOMA systems; Energy efficiency in NOMA systems; NOMA in vehicular communications. Dr. Sahar Hoteit Dr. Hyunbum Kim Dr. Omar Sami Oubbati Guest Editors
Last updated by Callie Liu in 2020-12-30
Special Issue on special issue on Access Control in the Internet of Things
Submission Date: 2021-10-15

link: https://www.mdpi.com/journal/sensors/special_issues/Access_Control_in_IoT Special Issue Information The Internet of Things (IoT) is a complex ecosystem that in the last several years has considerably improved our daily life style. In IoT networks, ubiquitous interconnected sensors, actuators, and devices produce a large amount of data, and the development of heterogeneous communication technologies allows them to exchange such data, thus enabling the creation of a number of innovative services. IoT technologies are applied in many domains, including smart home, smart city, and industrial and healthcare environments. Besides a large number of undoubted benefits, the widespread adoption of IoT technologies also raised security and privacy issues. Access control is a crucial aspect to be considered to guarantee the confidentiality and integrity of data and devices, and it is attracting increasing attention from both industry and academia. For instance, devices that actively monitor the human body’s vital signs or industrial systems deal with very sensitive and private data. Therefore, there is the necessity of increasing research activity about access control models and frameworks so as to guarantee, on the one hand, reliability and availability in order to ensure any urgent intervention in case of emergency, and on the other hand, restricted access to prevent any tentative corrupting, stealing, or disclosing of data. The aim of this Special Issue is to gather the latest research results concerning theories, methodologies, techniques, and new solutions for access control in IoT. In particular, this volume addresses the topic of access control in IoT while considering several dimensions: languages and models, requirements and architectural solutions, security and privacy issues, verification and validation techniques as well as application domains and perspectives. Researchers, experts, and scholars from both industry and academia are encouraged to present their recent achievements, joint collaborations, and research directions in this area. Topics of interest within access control in the IoT context include (but are not limited to): Vulnerability analysis and threat mitigation Data protection and privacy preservation Security and privacy requirements, analysis, and specification Architectures, protocols, and services in IoT Access Control models Context awareness of access control models Access Control policy languages Policy engineering Access Control enforcement techniques for IoT Validation and verification of access control systems Validation and verification of policy and policy languages Access Control frameworks and tools in IoT Distributed ledgers and blockchain applications for access control in IoT Access Control in Cyber-physical systems and ecosystems Access Control in Systems of Systems Access Control in industrial contexts Access Control in smart environments (city, home, campus, vehicles, etc.) Access Control for healthcare environment Access Control in IoT specific domains Perspectives, challenges, opportunities and issues of access control in IoT Dr. Francesca Lonetti (Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo", Area della Ricerca CNR di Pisa) Dr. Eda Marchetti (Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo", Area della Ricerca CNR di Pisa) Guest Editors
Last updated by Vicky Cai in 2020-12-31
Special Issue on Securing the Industrial Internet of Things
Submission Date: 2021-10-21

Website: https://www.mdpi.com/journal/sensors/special_issues/Securing_IIoT Dear Colleagues, The proliferation of the Internet of Things (IoT) has enabled rapid enhancements for the applications not only in home, business, and environment scenarios, but also in factory automation. Today, Industrial Internet of Things (IIoT) offers all the advantages of IoT to the industrial scenarios, for a wide range of applications from remote sensing/actuating to de-centralization/autonomy. In this Special Issue, the editor aims at presenting the IIoT and its place during the industrial revolution (Industry 4.0), while our world is being transformed into a better, comfortable, safer, automated, and sustainable one. This Special Issue will cover the cross-relations and implications of IIoT with existing wired/wireless communication/networking and safety technologies of the Industrial Networks, especially from a cybersecurity point of view. The cybersecurity-related needs/requirements of IIoT users (including GDPR-related implications and concerns) and the services that might address these needs will be a topic of interest. User privacy, data ownership, and proprietary information handling related to IIoT networks will also be investigated. The well-famed trio of cybersecurity, intrusion-prevention, -detection, and -mitigation will also be considered for IIoT networks. This Special Issue encourages authors from academia and industry to submit new research results related to cybersecurity of IIoT. The topics include but are not limited to the following: Cyber security of Cyberphysical systems (CPS) Digital twin Intelligent factory Industrial automation Internet-of-Things (IoT) Industrial Internet-of-Things (IIoT) Smart cities Smart factory Smart supply-chain management Cross-relations and implications of IIoT with (from a cybersecurity point of view): Process and building automation protocols for Industry 4.0: BACnet, CAN,DLSM/COSEM, DNP3, Fieldbus, HART, ISA 100.11a, IEC 62601,PROFIBUS, PROFINET, Modbus, Modbus+, M-Bus, SCADA,WirelessHART, X10 Wireless communications technologies for Industry 4.0: IEEE 802.15.4, LPWAN (LoRa, etc.), 6lowPAN, ZigBee, Z-Wave IIoT environments and privacy issues (GDPR point of view, etc.) Industrial applications using IIoT (from a cybersecurity point of view) Principles and techniques for cybersecurity of IIoT networks Data collection/preparation techniques for analysis regarding cyber security Technologies to be used Blockchain Digital signatures Homomorphic encryption and many more. Dr. Ismail Butun Guest Editor
Last updated by Callie Liu in 2020-12-30
Special Issue on Advanced Multi-Band Antennas and Millimeter-Wave Components
Submission Date: 2021-10-31

Dear Colleagues, Wireless communication is one of the fastest-growing fields of communication industry. This constant evolution fosters the antenna community to design new radiating systems capable of satisfying the market demands. Conventional antennas designed in a wireless communication system will operate in one frequency band. However, there is a need to design multiband or wideband antennas and components which can operate at multiple frequencies. In modern wireless communication systems, multiband antennas have derived rapidly increasing attention in which the downward compatibility and the roaming capability among multi-standards are demanded. The objective of the present special issue is to present the latest advances in the field of multiband antennas and components for wireless communications. Potential topics include, but are not limited to, multi-band antennas and also to multi-band millimeter wave components (like multiband polarizers, transmittarray, reflectarrays, frequency selective surfaces etc.). https://www.mdpi.com/journal/sensors/special_issues/multi_band_antennas Keywords Dual Band Multi Band Antennas Dual Band Antennas Multifrequency Antennas multiband antenna array design multiband operation dual-band satellite communication Dr. Emilio Arnieri Guest Editor
Last updated by James Su in 2021-04-26
Special Issue on Integrating Sensor Technologies in Educational Settings
Submission Date: 2021-10-31

https://www.mdpi.com/journal/sensors/special_issues/education_sensors Dear Colleagues, Just as sensor technologies are deeply impacting engineering and scientific practices, so too are they increasingly becoming integrated in educational settings to support innovative learning activities. The growing availability of low-cost, portable sensors can be deployed to collect real-time measurements of properties from the surrounding world, for example light, temperature, magnetism, acceleration, sound, and CO2. When coupled with microcontrollers (such as the micro:bit), sensor data streams can be easily programmed to control the behaviors of actuators and data displays, thereby making the invisible visible, inspectable, and actionable. This Special Issue will provide a forum for describing innovative approaches to using programmable sensor technologies in a range of educational settings. Papers are solicited on the general theme of this issue. Topics of interest include, but are not limited to: Reviewing the use of sensor technology in education settings; Describing the development of science and data science instructional materials that integrate sensor technology; Investigating how students engage in authentic scientific practices through exploring phenomena using sensor technology; Describing the development of real-time data displays of sensor data streams to support learning; Supporting the development of students’ computational thinking in sensor-based instructional materials; and Describing the development of physical computing learning environments integrating sensor technology. Prof. Dr. Mimi Recker Dr. Colin Hennessy Elliott Dr. Quentin Biddy Guest Editors
Last updated by Chloe Guo in 2021-04-26
Special Issue on special issue on Advances in Silicon Photonic Sensors
Submission Date: 2021-10-31

link: https://www.mdpi.com/journal/sensors/special_issues/Silicon_Photonic_Sensors Special Issue Information Silicon-based photonic biosensors can lead to major advances in point-of-care applications, food diagnostics, and environmental monitoring through the rapid and precise analysis of various substances. Different techniques for evanescent field sensing, optical trapping and label-free detection are proposed and experimentally evaluated during the last three decades. One major advantage of silicon is the availability of inexpensive fabrication technologies due to the compatibility with microelectronic technologies but also its flexibility in terms of surface functionalization. This Special Issue offers the possibility to gather recent improvements in the broad field of silicon-based photonic sensors. This includes bio and thermal sensing, novel detection methods and device concepts as well as fabrication techniques and packaging. Articles with latest experimental results as well as simulation studies are welcome. It is our pleasure to invite you to submit a manuscript for this Special Issue with the latest results, research lines, and trends that you are currently obtaining or following. Full papers, communications, and reviews are all welcome. Keywords Silicon photonic sensors Optical biosensors Sensor concepts and simulation Fabrication and packaging methods Porous silicon and novel materials Optofluidics Optical trapping Surface functionalization Label-free detection Photonic-plasmonic devices Prof. Dr. Fabio De Matteis (Università degli Studi di Roma Tor Vergata) Dr. Patrick Steglich (Technische Hochschule Wildau, University of Applied Sciences) Guest Editors
Last updated by Vicky Cai in 2020-12-31
Special Issue on Cyber Risk in the Industrial Internet of Things
Submission Date: 2021-11-01

https://www.mdpi.com/journal/sensors/special_issues/CR_IIoT Dear Colleagues, The next generation of industrial systems is going to be data-driven. Sensor data driven by the Internet of Things, both inside and outside of factories, will provide a digital thread connecting the factory floor with its products and customers. These “chatty” factories present immense opportunities for innovation, from improving products based on their use, to digital twins that fuse product redesign with intelligent re-manufacturing, all connected via industrial optimisation, and relationships between intelligent robotics and their human counterparts that are yet to be determined. The opportunities are clear. However, with digital innovation comes inherent cyber risk. Sensor data from the wild can only be used if it flows into decision-making processes linked to industrial modernisation. How do we know that the integrity of sensor data is not being corrupted, either deliberately or otherwise? What are the cyber risks to digital twins and how could these impact industrial elements of new production processes? How do we ensure that data-driven decisions are transparent and auditable? Will the convergence of technology in the wild with traditionally isolated operational technology prove too high-risk for widespread adoption? This Special Issue aims to provide a forum for the discussion of both opportunity and cyber risk arising from data-driven industrial Internet of Things, with a key focus on the critical factors that will both enable and restrict adoption. Prof. Dr. Pete Burnap Guest Editor
Last updated by Chloe Guo in 2021-04-26
Special Issue on Multi-UAV Systems: Networks, Services and Energy Management
Submission Date: 2021-11-15

https://www.mdpi.com/journal/sensors/special_issues/energy_UAV Dear Colleagues, The Guest Editors are inviting submissions to a Special Issue of Sensors on the subject area of “Multi-UAV Systems: Networks, Services and Energy Management”. The presence of Unmanned Aerial Vehicles (UAV), also known as drones, is rapidly growing regarding the capacity to provide a wide range of new commercial applications and services, such as emergency networks, healthcare, surveillance, disasters relief, search and rescue, agriculture, construction, cargo delivery, or even space exploration, and much more. UAVs can support and exploit 5G capabilities, with cost-effective points of presence, to provide Internet coverage and different network services to ground users. Implementations are facing important challenges. The duration of the services is usually longer than the battery life-time of the drones. New communication protocols are required. Softwarization technologies, such as NFV and SDN, are gaining traction to support the flexible provision of services on UAVs. Still, multiple technical challenges exist hindering their utilisation in this new study area. Machine Learning is envisioned as a fundamental technology in order to provide self-learning in centralized or distributed configurations. This Special Issue will deal with novel architectures, strategies, modelling, control, optimization and artificial intelligence for efficient energy consumption and management of UAV systems in terms of the services provided. Topics of interest for publication include, but are not limited to the following list: Architectures, infrastructure and systems. Energy policies for efficient consumption. Distributed configuration and management of UAV networks. NFV in UAV systems. SDN in UAV systems. Routing in UAV systems. Self-learning UAV systems. UAV systems aware protocols. Network infrastructures and instant-networks using UAVs. Security and privacy. Modelling, performance analysis and optimization. Energy aware services orchestration. Usage scenarios, testbeds and experimental prototypes. Machine learning and big data analytics for UAV. Network slicing in UAVs systems. Prof. Dr. Xavier Hesselbach Prof. Dr. Francisco Valera Prof. Dr. Iván Vidal Prof. Christian Tipantuña Guest Editors
Last updated by Chloe Guo in 2021-04-26
Special Issue on Advanced Laser Phototherapy: Sensing and Applications
Submission Date: 2021-11-30

Dear Colleagues, Lasers have been used in different therapy fields like dermatology, ophthalmology, dentistry and cancer therapy. Different physical processes are involved, depending on the wavelength being used, laser operation mode (continuous or pulsed), intensity and dose (or fluence) being applied. Ablation, photochemical and thermal interactions are the main mechanism than can be involved. Besides, the recent advances in nanotechnology have opened new possibilities for laser phototherapy techniques, using the phenomena of surface plasmon resonance to mediate the interaction processes. This Special Issue of Sensors will address the sensing techniques and methodologies used in the research and development of advanced laser phototherapy processes, including (but not limited to) guiding strategies, monitoring and evaluation sensing. Submissions regarding the development of sensors with potential application for laser phototherapy are also welcome. https://www.mdpi.com/journal/sensors/special_issues/laser_phototherapy Keywords laser phototherapy photothermal therapy photodynamic therapy sensing sensors imaging process monitoring instrumentation Dr. João M. P. Coelho Dr. Pedro Vieira Guest Editors
Last updated by James Su in 2021-04-26
Special Issue on special issue on Volatile Organic Compounds Detection with Optical Fiber Sensors
Submission Date: 2021-11-30

link: https://www.mdpi.com/journal/sensors/special_issues/VOCs_Optical_Fiber_Sensors Special Issue Information The detection of volatile organic compounds (VOCs) is a critical aspect in many fields. For instance, in many industries, these compounds present a high environmental impact, and their emissions need to be carefully controlled. On the other hand, in the food and beverage industry, these can be indicators of the products’ quality. Their presence can also be associated with environmental contamination, poor air quality, or even with certain human diseases. Many optical fiber-based sensors have been proposed in the last years to detect VOCs, and this is still a very active research field. This forthcoming Special Issue invites contributions regarding the research and development of new optical fiber sensors for the detection of VOCs, aiming at an advancement of the current state of the art. Short communications, original research experimental and theoretical papers, and review articles are welcomed for this Special Issue. These contributions can focus on, but are not limited to, the following topics: VOCs sensors based on new optical fiber geometries; Interferometric fiber sensors; Fiber gratings-based sensors; Optofluidic fiber sensors; Fiber sensors based on Vernier effect; Sensors based on whispering gallery modes; Detection of a single or multiple VOCs; Active or passive fiber sensors; New coating materials; Advanced sensing configurations. Dr. Marta S. Ferreira (i3N and Department of Physics, University of Aveiro, Campus Universitario de Santiago) Guest Editor
Last updated by Vicky Cai in 2020-12-31
Special Issue on special issue on Challenges in Energy Perspective on Mobile Sensor Networks
Submission Date: 2021-11-30

link: https://www.mdpi.com/journal/sensors/special_issues/Energy_Mobile_Sensor_Networks Special Issue Information Big data, machine learning, and artificial intelligence change our way of life significantly. New data collection and utilization are crucial to enhance these technologies, and IoT technology for this improvement is continually evolving. Much research has been conducted on data collection/transmission technology and edge computing for data merging/security, but most research and utilization were performed only on fixed sensors. Therefore, mobile sensor technology has become necessary to remedy the defect of fixed sensors and to place sensors properly. This Special Issue seeks a variety of technical activities for the mobile sensor network that will emerge, most importantly, in the data age. In this issue, we shall introduce technologies in various fields for mobile sensor networks such as mobile sensors, communication protocols, SDN (software-defined networking), NFV (network function virtualization), edge computing, wireless applications, and security, and provide opportunities to share new ideas with researchers around the world. Moreover, various new issues around computer science and electrical engineering, not limited to the above areas, will also be good material. Keywords Wired/wireless mobile sensors Sensor deployment/relocation protocols Sensor communication/security protocols Sensor fault-tolerant/energy-efficient protocols VNF, NFV based on SDN for WSNs Edge computing for WSNs Simulation/numerical techniques Machine learning applications Applied electromagnetics for wireless applications Prof. Dr. Moonseong Kim (Department of IT Convergence Software, Seoul Theological University) Prof. Dr. Byungseok Kang (Department of Electronics, Computing and Mathematics, University of Derby) Guest Editors
Last updated by Vicky Cai in 2020-12-31
Special Issue on  	Silicon Photonics: A Theme Issue in Honor of Professor Richard A. Soref
Submission Date: 2021-11-30

https://www.mdpi.com/journal/sensors/special_issues/SPATIH Dear Colleagues, Prof. Richard A. Soref is a research professor of engineering at the University of Massachusetts, United States. Prof. Soref is a well-known expert in photonics and the science of light and considered by many as the "father of silicon photonics". Prof. Soref's career in basic and applied research spans more than 50 years. Initially inspired by the fields of science, engineering, and materials in his youth, Prof. Soref acquired a radio license to become the youngest amateur radio operator in Wisconsin at the age of 13. During his career, he has contributed more than 550 peer-reviewed papers, authored chapters in eleven books, and served on the editorial board of Optical Engineering. He holds 54 U.S. patents. His work includes the invention of opto-electronic integration in silicon, significant contributions to SiGeSn material development and, since 1985, visionary, fundamental contributions to the science and technology of silicon photonics. Optical communications and sensing technology were also advanced by Prof. Soref's innovations in waveguide-circuit integration, electro-optical modulation, photonic crystals, nonlinear optics, matrix switching, optical logic, laser physics, plasmonic-photonics, microwave photonics, and infrared detection. Active in multiple committees and organizations related to his work, Prof. Soref founded the Institute of Electrical and Electronics Engineers (IEEE) International Group IV Photonics Conference in 2004, which granted him a Lifetime Achievement Award in 2010. A Life Fellow of IEEE, he is also an Elected Fellow of the National Academy of Inventors, the Optical Society of America, and the Institute of Physics, among others. He has also received multiple awards during his tenure, including the Achievement Medal of the Institution of Engineering and Technology in 2019, the Marquis Who’s Who Lifetime Achievement Award in 2018, the U.S Air Force Basic Research Award in 1991, the Charles E. Ryan Memorial Award from Rome Laboratory in 1988, and several Air Force Office of Scientific Research Star Team Leader Awards between 2005 and 2011. This Special Issue is dedicated to celebrating the career of Prof. Richard A. Soref in honor of his contributions in the field of silicon photonics. It will cover a selection of recent research and review articles related to the science and technology of silicon photonics, optical communications and sensing, nonlinear optics, laser physics, and infrared detection. Dr. Vittorio M.N. Passaro Dr. Francesco De Leonardis Guest Editors
Last updated by Daisy Wang in 2020-12-31
Special Issue on special issue on Biosignal Sensing and Processing for Clinical Diagnosis
Submission Date: 2021-12-03

link: https://www.mdpi.com/journal/sensors/special_issues/Biosignal_Sensing Special Issue Information Biosignals have a long history of use in the clinical diagnosis and follow-up of multiple pathologies, as is the case of the electrocardiogram in cardiology. Advances in sensing and computing, as well as the emergence of artificial intelligence, have driven a great advance in this field, expanding the diagnostic spectrum of traditionally used biosignals, improving biosignal quality, and opening the door to the use of new biosignals such as biochemical or biomagnetic signals. Obtaining valuable and clinically useful information is still challenging, involving the development and/or selection of the appropriate biosignal sensing systems and algorithms for automatic signal segmentation, denoising or artifact removal, signal parameterization, and feature selection. Recently, the challenge of obtaining information useful for clinical diagnosis has been addressed by the development of decision support systems via machine or deep learning. It is important to consider all of these developments in the context of their implementation in clinically friendly systems that minimize patient discomfort, are simple to use, and provide information that is easily interpretable by physicians in near real time. The aim of the Special Issue “Biosignal Sensing and Processing for Clinical Diagnosis” is to collect a compendium of articles about new trends and advances in biosignal sensing and processing as well as their use in clinical decision support systems. We look forward to your participation in this Special Issue. Topics of interest include, but are not limited to, the following: New trends in biosignal sensing; Biosignal processing and analysis: electrocardiographic, myoelectric, electroencephalographic, photoplethysmographic, gastric, biochemical, or biomagnetic signals, among others; Applications of machine learning, deep learning, and artificial intelligence in using biosignals for clinical diagnosis. Keywords biosignals biomedical sensors biomedical signal signal processing feature extraction machine learning deep learning Dr. Gema Prats Boluda (Centro de investigación e Innovación en Bioingeniería (Ci2B), Universitat Politècnica de València) Dr. Javier Garcia-Casado (Centro de investigación e Innovación en Bioingeniería (Ci2B), Universitat Politècnica de València) Dr. Yvonne Tran (Centre for Healthcare Resilience and Implementation Science, Australian Institute of Health Innovation, Macquarie University) Dr. Yiyao Ye-Lin (Centro de investigación e Innovación en Bioingeniería (Ci2B), Universitat Politècnica de València) Dr. José Luis Martinez de Juan (Centro de investigación e Innovación en Bioingeniería (Ci2B), Universitat Politècnica de València) Dr. Dongmei Hao (College of Life Science and Bioengineering, Beijing University of Technology ) Guest Editors
Last updated by Vicky Cai in 2020-12-31
Special Issue on Advances and Applications of Micro/Nano-Electronic Sensors
Submission Date: 2021-12-15

Special Issue "Advances and Applications of Micro/Nano-Electronic Sensors" Website: https://www.mdpi.com/journal/sensors/special_issues/MicroNanoElectronicSensors Deadline for manuscript submissions: 15 December 2021 Dear Colleagues, Wearable electronics have started to gain momentum because of their essential role in improving the quality of life for various patients and healthy individuals. The function and performance of integrated NEMS/MEMS systems depend on the design of nano-/microsystems, choice of materials, manufacturing approaches, packaging, and device integration methods. It is also of high interest to investigate the interrelationships between material properties and processing, device/system structure, and the mechanical, electrical, optical, or (bio)chemical behavior of devices/systems. Resonant sensors are a type of sensor that relies on the measurement of resonant frequency to detect a variety of physical parameters such as pressure, temperatures, viscosity, gas concentrations, accelerations, etc. This type of sensor has drawn a significant amount of attention due to its excellent stability, resolution, and accuracy. In addition, this type of sensor allows devices to be easily connected to digital systems, which is required for its effective employment as a measurement device. Keywords MEMS sensors piezoelectric sensors radio frequency sensors acoustic sensors microsystem design device/system structure fabrication techniques biomedical applications mechanical, electrical, optical, or (bio)chemical behavior of devices/systems Prof. Dr. Huanyu Cheng Prof. Dr. Haifeng Zhang Dr. Zhiqun (Daniel) Deng Guest Editors
Last updated by Callie Liu in 2020-12-30
Special Issue on MEMS and NEMS Sensors
Submission Date: 2021-12-31

Special Issue "MEMS and NEMS Sensors" Website: https://www.mdpi.com/journal/sensors/special_issues/MEMS_NEME_sensors Deadline for manuscript submissions: 31 December 2021 Dear Colleagues, The manufacturing and integration of autonomous and embedded sensors through a combination of micro- and nano-system technologies have been revolutionizing self-powered, high bandwidth devices for advance manufacturing (AM), artificial intelligence (AI), Internet of Things (IoT), and health technologies. More specifically, nano- and micro-electro-mechanical-systems (N/MEMS) sensors are the building blocks for a vast range of applications, from continuous real-time health (wearable) and environmental monitoring (gas, biomolecules, pressure, temperature, etc.) to enabling embedded mobile Internet services (wireless), including smart/connected cars and unattended vehicles (UAV) (inertial). As these devices have numbered in the tens of billions, the potential for disruptive innovation has been immense. Integration of nano- and micro-sensors-which are functionalized using emerging materials to complementary metal-oxide-semiconductors (CMOS) and microfluidics systems, and their electro-mechanical packing are very challenging. Because, the integration and packing require the multiple deposition of layers of different dielectrics and metals, the atomic mismatch between these layers, acting as electron trap, increases ohmic resistance, and creates noise and reduces sensitivity, selectivity and responsivity; and increases detection time. This Special Issue aims to introduce the manufacturing, packaging and integration of autonomous and embedded sensors through a combination of micro- and nano-system. Topics in general include, but are not limited, to: - Autonomous and embedded sensors: design, manufacture, packaging and reliability - Biosensors (photonic, electrical, chemical) and their integration to MEMS, CMOS and microfluidic systems for COVID-19 and other (future) pandemics’ roteins/metabolites/analytes - Sensor interconnectors/interfaces and their testing - Graphene-based nano-sensors - Electronic circuits for MEMS nano-sensor modulation - Nano-electro-mechanical sensors Prof. Dr. Mustafa Yavuz Guest Editor Keywords N/MEMS-sensors sensor integration to N/MEMS CMOS and microfluidic systems electronic circuits for N/MEMS nano-sensor modulation bifurcation sensing sensor functionalization Nano-electro-mechanical sensors PeCOD COVID-19
Last updated by Callie Liu in 2020-12-30
Special Issue on Assistive Robots for Healthcare and Human-Robot Interaction
Submission Date: 2021-12-31

Dear Colleagues, Assistive technologies like Assistive Robots (AR) are being considered as enablers to support the process of care giving, potentially enhancing patient well-being and decreasing caregiver workload. Currently, it needs to deepen the research about person-centered care, multimodal interaction, multimodal data collection, caregiver expectancy model to improve AR acceptability. In light of these assumptions, the Human-Robot Interaction (HRI) field is devoted to understanding, designing, and assessing the robotic systems used by human being. By definition, the interaction implicates the communication. In light of this assumption, research in the HRI field is increasingly focused on the development of robots equipped with intelligent communicative abilities, in particular speech-based natural-language conversational abilities. These efforts directly relate to the research area of computational linguistics, generally defined as “the subfield of computer science concerned with using computational techniques to learn, understand, and produce human language content”. The advances and results in computational linguistics provide a foundational background for the development of so-called Spoken Dialogue Systems, i.e., computer systems designed to interact with humans using spoken natural language. The ability to communicate using natural language is a fundamental requirement for a robot that interacts with human being. Then, spoken dialogue is generally considered as the most natural way for social human-robot interaction. The sensing technologies represent a key role in the HRI and new approaches or application of existing ones in novel way could be really significant in facilitating the improvement of this field and consequently in all the sub-fields related to it. The central focus of this Special Issues will be to advance novel technologies applied in healthcare processes that have shown exceptional promise in models of HRI though the use of new sensors or methodologies capable to adapt, combine or improve the existing ones. The first important question concerns the modalities needed to sense the emotional state of people by the robot. Secondly, there is the problem of modelling the interaction between human and robot, not only on a haptic level, but also on an emotional level. Dr. Grazia D'Onofrio Dr. Daniele Sancarlo Guest Editors
Last updated by James Su in 2021-04-26
Special Issue on Advanced Quantum Diamond Sensors and Applications
Submission Date: 2021-12-31

Dear Colleagues, There is as growing body of knowledge demonstrating the quantum sensing capabilities of atomic scale defects within diamond. Over the past decade significant advances in the science and technology underpinning quantum diamond sensors have been realised opening up a broad range of measurement capabilities. To date methodologies for ultra-sensitive detection of magnetic fields, electric fields and temperature have been widely reported. Globally, significant research efforts and investment are being directed towards the further development of quantum diamond sensors and demonstration of their measurement capabilities. There is tremendous potential for deployment of quantum diamond sensors in electrical and thermal monitoring in electric vehicle batteries, high resolution magnetic resonance spectroscopy to uncover the chemical structures at a single molecule level, novel microwave sensors for use in the telecommunication sector, characterisation of future materials including spintronics devices and nanomaterials. Overall, quantum diamond sensors provide unprecedented measurement sensitivity and are poised to become essential tools across many sectors. This Special Issue on “Advanced Quantum Diamond Sensors and Applications” has the objective of showcasing current and emerging technologies that exploit the quantum assisted sensing capabilities of diamond. Reports describing new methodologies, materials, technical developments and applications are particularly welcome. https://www.mdpi.com/journal/sensors/special_issues/quantum_diamond_sensors Keywords biological imaging diamond quantum sensors optical microscopy healthcare technologies Prof. Dr. Melissa L. Mather Prof. Dr. Philippe B. Wilson Guest Editors
Last updated by James Su in 2021-04-26
Special Issue on Camera Calibration and 3D Reconstruction
Submission Date: 2021-12-31

Dear Colleagues, The importance of accurate image-based assessment of 3D objects and scenes is rapidly growing in the fields of computer vision (cf. AR/VR, autonomous driving, aerial surveillance, etc.) and optical metrology (photogrammetry, fringe projection, deflectometry, etc.). As the performance of digital sensors and optics approaches physical limits, uncertainties associated with models of imaging geometry, calibration workflows and data types, pattern recognition algorithms etc. directly affect numerous applications. We are pleased to invite you to contribute manuscripts to this Special Issue. It addresses the metrological aspects of modeling, characterizing, and using digital cameras in the context of 3D measurements, as well as novel analytic (e.g., visualization) tools and techniques facilitating robust and reliable camera-based measurements. Both original research articles and reviews are welcome. https://www.mdpi.com/journal/sensors/special_issues/camera_calibration_3D_reconstruction Keywords camera calibration geometrical camera models image-based 3D reconstruction uncertainties in optical 3D measurements shape-from-X techniques high-precision camera-based measurements non-conventional imaging systems for 3D measurements computational imaging for 3D measurements We look forward to receiving your contributions. Please do not hesitate to contact us if you have any comments or questions. Dr. Alexey Pak Prof. Dr. Steffen Reichel Dr. Jan Burke Guest Editors
Last updated by James Su in 2021-04-26
Special Issue on special issue on Cyber-Security-Based Internet of Things for Smart Homes
Submission Date: 2021-12-31

link: https://www.mdpi.com/journal/sensors/special_issues/Cyber-Security_IoT_Smart_Homes Special Issue Information The rapidly evolving technology of the Internet of Things introduces new cybersecurity challenges, especially where installations handle and process personal and private data. As such, smart homes constitute an ecosystem which is prone to new complex cyberattacks and attractive to attackers. This Special Issue aims to present recent advances in new techniques for the cyber defense of smart homes, by taking advantage of recent developments in machine, deep and federated learning, distributed ledger technologies such as blockchain, as well as behavioral monitoring of IoT devices. Topics of interest include but are not limited to the following: Cybersecurity architectures for IoT and smart homes; Cybersecurity analytics platforms for IoT; Blockchain for IoT and smart homes; Machine and deep learning for the security of IoT; Behavioral monitoring of IoT; Federated IoT smart home infrastructures with focus on security and privacy; Cyberthreat intelligence; AI-based methods for malware and ransomware; Privacy and trust in IoT. Keywords Smart homes Internet of Things Cyber security Privacy Intrusion detection systems Network behavior analysis Machine/deep/federated learning Distributed ledger technologies Dr. Konstantinos Votis (Information Technologies Institute, Centre for Research and Technology Hellas) Dr. Konstantinos M. Giannoutakis (Information Technologies Institute, Centre for Research and Technology Hellas) Dr. Nikolaos Dimitriou (Information Technologies Institute, Centre for Research and Technology Hellas) Guest Editors
Last updated by Vicky Cai in 2020-12-31
Special Issue on special issue on Human Centered Artificial Intelligence: Putting the Human in the Loop for Implementing Sensors Based Intelligent Environments
Submission Date: 2021-12-31

SI LINK: https://www.mdpi.com/journal/sensors/special_issues/Artificial_Intelligence_Implementing_Sensors Special Issue Information: This Special Issue aims to solicit original and high quality research articles that consider the current evolvement of AI approaches under a human-centric approach in the development of intelligent environments. Exceptional contributions that extend previously published work will also be considered, provided that they contribute at least 60% new results. Authors of such submissions will be required to provide a clear indication of the new contributions and explain how this work extends the previously published contributions. Topics may include, but are not limited to, the following: Active machine learning Adaptive personal AI systems Causal learning, causal discovery, causal reasoning, causal explanations, and causal inference Cognitive computing Decision making and decision support systems Emotional intelligence Explainable, accountable, transparent, and fair AI Explanatory user interfaces and HCI for explainable AI Ethical and trustworthy AI Federated learning and cooperative intelligent information systems and tools Gradient-based interpretability Interaction modalities and devices: visual, 2D/3D, augmented reality, simulations, digital twin, conversational interfaces, and multimodal interfaces Interactive machine learning Interpretability in reinforcement learning Human–AI interactions and intelligent user interfaces Human–AI teaming Natural language generation for explanatory models Processes, tools, methods, user involvement, user research, evaluation, AI technology assessment and customization, and standards Rendering of reasoning processes Self-explanatory agents and decision support systems Usability of human–AI interfaces Dr. Constantine Stephanidis (1. Foundation for Research and Technology Hellas (FORTH), Institute of Computer Science (ICS), Human Computer Interaction Laboratory (HCI Lab); 2. Department of Computer Science, University of Crete) Dr. George Margetis (Foundation for Research and Technology Hellas (FORTH), Institute of Computer Science (ICS), Human Computer Interaction Laboratory (HCI Lab)) Guest Editors
Last updated by Vicky Cai in 2021-01-08
Special Issue on Multistage Manufacturing Processes in the Industry 4.0 for Zero-Defect Products
Submission Date: 2022-01-01

https://www.mdpi.com/journal/sensors/special_issues/mul_manu Dear Colleagues, One of the most important challenges in modern industry is the implementation of manufacturing systems that are capable of producing “zero-defect” products. In most cases, manufacturing consists of a sequence of stages where manufacturing operations are sequentially conducted to manufacture a part or product. These multistage manufacturing processes (MMP) show complex error interactions among stages, which makes it difficult to control product quality, and tasks such as predictive maintenance, process control, quality assurance and fault diagnosis are challenging. Under the new paradigm of Industry 4.0, sensing networks based on IIoT and the implementation of digital twins based on engineering and data-based models is set to have a major impact on these processes. The implementation of this new paradigm is expected to lead to manufacturing systems with self-adjust and self-optimization capabilities, optimal decision making based on simulated-driven strategies, correction actions for error compensation, optimal predictive maintenance actions, and so on. In this Special Issue, we encourage scholars to share recent advances in the field of MMPs and Industry 4.0. Investigations related to in-process sensing and data analytics, IIoT, fault diagnosis, digital twins, predictive maintenance, quality assurance and quality control are welcome, especially those focused on strategies for “zero defect” manufacturing. Prof. Dr. Jose Vicente Abellan-Nebot Prof. Dr. Ignacio Peñarrocha-Alós Guest Editors
Last updated by Chloe Guo in 2021-04-26
Special Issue on Sensors for Digital Construction
Submission Date: 2022-01-01

https://www.mdpi.com/journal/sensors/special_issues/Digi_Constru Dear Colleagues, Detailed insights into the ongoing processes of construction projects are a prerequisite for an efficient management of time, costs, and resources. However, providing relevant information requires the analysis of vast amounts of data. A consistent digitization throughout all phases of a project facilitates a proper aggregation of these data, as well as an automated evaluation. While digital building models already support decision making during project planning, other domains are only sparsely digitized. The use of sensors helps to advance digitization in construction through the automated collection of time-dependent data. It allows for a continuous localization of resources and materials as well as the monitoring of construction machines and their states. This enables a digital monitoring of construction projects through their entire life cycle and supports the management in optimizing workflows, scheduling maintenance, improving safety, and so on. This Special Issue focuses on the application of sensors in construction-related domains and the processing of the collected data. Relevant topics include but are not limited to: Digital twin Internet of Things Safety Productivity Maintenance Prof. Dr. Markus König Guest Editor
Last updated by Chloe Guo in 2021-04-26
Special Issue on Machine Learning in Human Activity Recognition
Submission Date: 2022-01-31

https://www.mdpi.com/journal/sensors/special_issues/ML_HAR Dear Colleagues, Human Activity Recognition (HAR) using pervasive and body-worn sensors has become a major research field with numerous practical applications. At the heart of most HAR systems lies the automated analysis of sensor readings, for which machine learning techniques are typically applied. With the explosion of research in the core machine learning area, numerous methods have been developed that are also of value for the HAR community. However, HAR comes with its own challenges for machine learning methods, such as challenging data quality, including sensor noise, faulty sensor readings, or ambiguities; often only very small datasets come with ground truth annotation; computational challenges for performing activity recognition in real time and on severely resource constrained devices; open ended activity recognition; and continuous adaptation of recognition systems, to name but a few. This Special Issue aims to provide an overview of the state-of-the-art and latest developments in the field of machine learning for human activity recognition. Prof. Dr. Thomas Ploetz Dr. Yu Guan Prof. Dr. Daniel Roggen Guest Editors
Last updated by Chloe Guo in 2021-04-26
Special Issue on Wearables and Modern Technology for Sports Medicine: The Digital Age of Athletes
Submission Date: 2022-02-01

https://www.mdpi.com/journal/sensors/special_issues/wearable_sports Dear Colleagues, Sports engineering has led to modern technology substantially increasing and advancing in the field of sport and exercise medicine over the past decade. The interest in sports engineering aligns with the increased provision for sports medicine within professional and amateur sport, with multidisciplinary teams of professionals now employed to keep athletes healthy and continuing to perform to a high standard: medics, physiotherapists, nutritionists, strength and conditioning experts, etc. Technological development is creating more objective and accurate assessment tools that can augment the clinical reasoning/judgement that sports medicine decisions typically rely on. Digital health approaches are being developed at a rapid pace, with increasingly smaller and more discrete sensors/devices/applications that are able to collect data on all aspects of athlete health and performance on and off the field of play (in or out of competition). This Special Issue will focus on the technology that has been applied within sporting contexts and relevant populations to support sports medicine, particularly the following topics: Wearable sensing and mobile technology; Concussion assessment and management; Diet and nutrition tracking or intervention; Physical activity or performance metrics; Cardiovascular screening; Lower limb injury and player biometrics; Pitch-side assessment and management; Injury or performance evaluation and management; Novel technology in amateur and elite sport. Dr. Sam Stuart Dr. Steven Marshall Dr. Alan Godfrey Guest Editors
Last updated by Chloe Guo in 2021-04-26
Special Issue on Prototyping of Industrial IoT Solutions
Submission Date: 2022-02-15

https://www.mdpi.com/journal/sensors/special_issues/proto_IIoT Dear Colleagues, The Industrial Internet of Things (I-IoT) is widely considered a key enabling technology of the fourth industrial revolution (I-4.0). The bridging of industrial assets with cloud infrastructures will allow the generation of many digital twins. I-IoT will fuel a multitude of innovation processes aimed at optimizing industrial processes and methods. However, the introduction of industrial IoT technologies into factories is a complex and cumbersome activity. Researchers, technicians, and entrepreneurs interested in bringing IoT into shop floors need to deal with reliability, scalability, compatibility, and security issues that are more complex in industrial environments than in consumer and domestic scenarios. Evolution from IoT to Industrial IoT requires a dedicated design process where the prototyping phase becomes crucial. Companies need to reduce the investment required for testing I-4.0 and I-IoT solutions, thus increasing the Return of Investment (ROI) while minimizing the impact on production and organization. Moreover, Industry 4.0 pushes companies and factories toward lean production strategies where fast prototyping in R&D processes is mandatory. For this reason, there is a strong need for reliable and secure fast prototyping solutions for Industrial IoT that, while guaranteeing a fast and cost-effective implementation of proof of concept, also guarantee future scalability toward extended, secure, stable and professional industrial setups. Prof. Dr. Daniele Mazzei Prof. Dr. Dorota Stadnicka Dr. Joan Navarro Prof. Dr. Chrysostomos Stylios Prof. Dr. Giuseppe Lannaccone Guest Editors
Last updated by Chloe Guo in 2021-04-26
Special Issue on Advanced Sensor Networks/Seismic Networks and Monitoring for Earthquakes and Phenomena Having a Seismic Signature 
Submission Date: 2022-03-12

Dear Colleagues, The study of earthquakes is of global interest, mainly because the comprehension of such phenomena is useful to safeguard human lives. To this aim, tools (such as seismic networks and arrays, but also data analysis procedures) by which detect and localize from small to large magnitudes earthquakes quickly and accurately are fundamental. Since the last few years, advances in technology have allowed seismologists to design seismic networks more and more sophisticated (with boreholes or ocean bottom sensors). At the same time, potentially interesting seismological information can be obtained by instruments developed for different purposes (e.g., optical fiber, geophones, rotational sensors). Besides earthquakes, there are many phenomena that we are able to record with seismic networks; they are both of natural origin (as volcanic eruptions, landslides, sinkholes, weather events, meteorite impacts), and anthropogenic (as underground fluid injections, quarry blasts, nuclear explosions, etc.). In this special issue we aim to collect scientific papers focused on advanced techniques of seismic monitoring or data analysis of natural and anthropogenic events. Also, contributions from studies carried out by ‘unconventional’ seismic networks are welcome. tectonic and induced earthquakes fiber DAS networks no earthquakes seismic signature events rotational sensors off-shore seismicity location improvements seismic information from unconventional sensors Dr. Mario Anselmi Dr. Aladino Govoni Dr. Cristina Totaro Dr. Maria Adelaide Romano Guest Editors
Last updated by James Su in 2021-04-26
Special Issue on Data and Privacy Management in Sensor Networks
Submission Date: 2022-03-30

Dear Colleagues, Recent years have witnessed a widespread interest in innovative sensor networks capable of providing valuable data for various applications (e.g., home automation, energy management), the connected objects and environments impact numerous application domains. From smart homes and buildings to cities, vehicle networks, and electrical grids, they have become a novel trend that is revolutionizing how people interact with their surroundings, how they accomplish their daily tasks in the workplace, and how they handle their health security, and safety. Sensor networks markets are currently booming and are projected to continue their growth for the years to come. The rising interest in intelligent connected environments (e.g., smart buildings, cities, factories) and the evolution of sensors, data management/communication technologies have paved the way for exciting and valuable applications that help users in their everyday tasks (e.g., increasing comfort, reducing energy consumption). Indeed, the sensor network ecosystem have made it easy to collect and exchange a large amount of data, connect heterogeneous systems, create complex systems for new forms of collaboration and interoperability. Typically, the sensed data are transmitted to the edge nodes, or directly to the cloud/server where it will be stored, indexed, processed and analysed to offer a new class of advanced services, such as envirenement monitoring, objects tracking, event detection, advanced data analytics, etc. Despite the progress made, however, data and privacy management in sensor networks remains a core and challenging issues. In fact, due to the nature of sensor networks, there exist complexity in gathering, aggregation, indexing, storage, processing and analysing big data generated by resource-constrained sensor nodes per unit time. Furthermore, sensor networks also impose new challenges related to knowledge discovery and decision-making automation, security, privacy, and trust. This special issue will promote the state-of-the-art research covering all aspects of the data and privacy management in sensor networks. High quality contributions addressing related theoretical and practical aspects are expected. The topics of interest for this special issue include, but are not limited to : Modelling, simulation of sensor networks Architecture and Protocols for sensor networks Data gathering, storage and aggregation in sensor networks Data processing, indexing and discovery in sensor networks Data analytics solutions for sensor networks Knowledge discovery and decision-making automation in sensor networks Modelling, analysis, simulation, and verification of security, privacy, and trustworthiness for sensor networks Detection, evaluation, and prevention of threats and attacks in sensor networks Data security, privacy, and trustworthiness in sensor networks https://www.mdpi.com/journal/sensors/special_issues/data_privacy_management_sensor_network Dr. Richard Chbeir Dr. Taoufik Yeferny Guest Editors
Last updated by James Su in 2021-04-26
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