Conference Information
IPSN 2024: International Conference on Information Processing in Sensor Networks
https://ipsn.acm.org/2024/
Submission Date:
2023-10-24
Notification Date:
2024-01-20
Conference Date:
2024-05-13
Location:
Hong Kong, China
Years:
23
CCF: b   CORE: a*   QUALIS: a1   Viewed: 39143   Tracked: 91   Attend: 11

Call For Papers
The ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) is the leading annual forum on research at the intersection of networked embedded sensing, control, and systems design. IPSN brings together researchers from academia, industry, and government to present and discuss recent advances in both theoretical and experimental research on all aspects of networked systems of sensors and actuators. Its scope includes signal and image processing, information and coding theory, databases and information management, distributed algorithms, networks and protocols, wireless communications, collaborative objects, the Internet of Things, machine learning, mobile and social sensing, and embedded systems design. Of special interest are contributions at the confluence of multiple of these areas

IPSN 2024 is co-located with the CPS-IoT Week, the premier venue for research and development of cyber-physical systems. IPSN is co-sponsored by both the ACM and IEEE, and it continues to emphasize research that bridges multiple research communities. IPSN is interested in all aspects of sensor networks, ranging from traditional topics such as networking to more recent developments such as embedded machine learning, RF sensing and computer vision.

Topics of interest include, but are not limited to:

    Systems, Architectures, and Tools
        Sensor data storage, retrieval, processing
        Network and system architectures and protocols
        IoT gateway platform architecture and services
        Wearable systems and data processing algorithms
        Programming models, languages, and systems
        Programming models for IoT ensembles
        Modeling, simulation, and measurement tools
        Operating systems and runtime environments
        Discovery, coordination, and use of IoT services
        IoT reliability, adaptability, and dependability
        Technical assessment of emerging IoT standards
    Algorithms, Data, and Theory
        Localization, synchronization, RFID, and RF sensing
        VLC and visible light based sensing
        Data related issues, such as methods, tools, and analysis
        Coding, compression, and information theory
        Theoretical foundations and fundamental bounds
    Applications
        Applications in health, wellness & sustainability
        Applications in smart cities and urban health
        Experiences, challenges, comparisons of platforms
        Sensor-enabled autonomous vehicle platforms and algorithms
        Outdoor, wide-area, or crowdsourced sensing systems
        Sensor data processing for augmented and virtual reality applications
    Security and Privacy
        Security, trustworthiness, and privacy for IoT systems
        Fairness, equity, and transparency issues in IoT and CPS
    Machine Learning
        Large foundational models (LFMs) for sensor data analytics, distillation of LFMs to edge platforms
        Machine learning, deep, federated and multimodal learning on sensor data
        Novel embedded machine learning algorithms for resource-constrained and mobile platforms
        New hardware and system design to enable machine learning on sensor data
Last updated by Dou Sun in 2023-10-10
Acceptance Ratio
YearSubmittedAcceptedAccepted(%)
2019912527.5%
2018822226.8%
20171041918.3%
20161172319.7%
20151082725%
20141112018%
20131152420.9%
20121472215%
20111222722.1%
20101172017.1%
20091172117.9%
20081263023.8%
20071702615.3%
20061652515.2%
20041452517.2%
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