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IPSN 2021 : 20th ACM/IEEE Intl. Conf. on Information Processing in Sensor Networks

Nashville, Tennessee, USA
Event Date: May 18, 2021 - May 21, 2021
Abstract Submission Deadline: Oct 19, 2020
Submission Deadline: Oct 26, 2020

About

The International Conference on Information Processing in Sensor Networks (IPSN) is a leading annual forum on research in networked sensing and control, broadly defined. IPSN brings together researchers from academia, industry, and government to present and discuss recent advances in both theoretical and experimental research. Its scope includes signal and image processing, information and coding theory, databases and information management, distributed algorithms, networks and protocols, wireless communications, collaborative objects and 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.

Call For Paper

Topics of interest include, but are not limited to:

  • Sensor data storage, retrieval, processing
  • Coding, compression, and information theory
  • Theoretical foundations and fundamental bounds
  • Network and system architectures and protocols
  • IoT gateway platform architecture and services
  • Outdoor, wide-area, or crowdsourced sensing systems
  • Localization, synchronization, RFID, and RF sensing
  • Programming models, languages, and systems
  • Programming models for IoT ensembles
  • Modeling, simulation, and measurement tools
  • Operating systems and runtime environments
  • Applications in health, wellness & sustainability
  • Applications in smart cities and urban health
  • Experiences, challenges, comparisons of platforms
  • Discovery, coordination, and use of IoT services
  • Security and privacy
  • IoT reliability, adaptability, and dependability
  • Technical assessment of emerging IoT standards
  • Wearable systems and data processing algorithms
  • Sensor-enabled drone / autonomous vehicle platforms and algorithms
  • Machine learning and deep learning on sensor data
  • New hardware and system design to enable machine learning on sensor data
  • Novel embedded machine learning algorithms
  • Data related issues, such as methods, tools, and analysis
  • Fairness, equity, and transparency issues in IoT and CPS
  • Computer vision for resource-constrained and mobile platforms

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