Self-Powered IoT Sensor Node with In-situ Data Analytics and Energy-Aware End-to-End Real-Time Optimization

  • Authors:
    Shreyas Sen (Purdue), Arijit Raychowdhury (Georgia Tech)
    Publication ID:
    P091005
    Publication Type:
    Annual Review
    Received Date:
    29-May-2017
    Last Edit Date:
    30-May-2017
    Research:
    2720.001 (Georgia Institute of Technology)

Abstract

With the proliferation of distributed sensors and Internet of Thing end-nodes, aggregate data transfer to the backend servers in the cloud is expected to become prohibitively large which not only results in network congestion, but also high energy expenditure of sensor nodes. This motivates in-situ data analytics that can perform context-aware acquisition and processing of data; and transmit data only when required. This talk presents a camera based wireless sensor node with in-sensor computation and wireless communication and end-to-end system optimization. Depending on the amount of information content and wireless channel quality, the system chooses the minimum-energy operating point by dynamically adjusts processing depth (PD) and power amplifier (PA) gain while reducing data volume the network has to handle. We demonstrate a complete end-to-end system and measure 3:7Ă— reduction in energy consumption compared to a baseline design where only rudimentary image compression is performed.

Past Events

  Event Summary
31–1 May 2017–June 2017
GRC
GRC
2017 System Level Design Review
Wednesday, May 31, 2017, 8 a.m. — Thursday, June 1, 2017, 5 p.m. ET
Ann Arbor, MI, United States

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