In-Sensor Analytics and Energy-Aware Self-Optimization in a Wireless Sensor Node

  • Authors:
    Ningyuan Cao (Georgia Tech), Saad Bin Nasir (Georgia Tech), Shreyas Sen (Purdue), Arijit Raychowdhury (Georgia Tech)
    Publication ID:
    P091033
    Publication Type:
    Paper
    Received Date:
    30-May-2017
    Last Edit Date:
    31-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 a the sensor nodes. This motivates in-sensor data analytics that can perform context-aware acquisition and processing of data; and transmit data only when required. This paper presents a camera based wireless sensor node with in sensor computation, wireless communication and end-to-end system optimization. Depending on the amount of information content and the wireless channel quality, the system chooses the minimum energy operating-point by dynamically adjusting the processing depth (PD) and power amplifier (PA) gain. 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.

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