CAREER: Building Energy-Efficient IoT Frameworks - A Data-Driven & Hardware-Friendly Approach Tailored for Wearable Applications

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Sensor energy efficiency is the top critical concern that hinders long-term monitoring in energy-constrained Internet-of-things (IoT) applications. Conventional compressive sensing techniques fail to achieve satisfactory performance in IoT and especially wearable applications due to the lack of prior knowledge about signal models and the overlook of individual variability. The research goal of this CAREER plan is to develop a data-driven and hardware-friendly IoT framework to fundamentally address the unmet energy efficiency need of IoT and especially wearable applications.

  • 1652038
  • Arizona State University
  • CPS-PI Meeting 2017
  • Poster
  • Posters (Sessions 8 & 13)
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