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arXiv · 1701.05599

Energy-efficient Analog Sensing for Large-scale, High-density Persistent Wireless Monitoring

Vidyasagar Sadhu·Xueyuan Zhao·Dario Pompili
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Abstract

The research challenge of current Wireless Sensor Networks~(WSNs) is to design energy-efficient, low-cost, high-accuracy, self-healing, and scalable systems for applications such as environmental monitoring. Traditional WSNs consist of low density, power-hungry digital motes that are expensive and cannot remain functional for long periods on a single charge. In order to address these challenges, a \textit{dumb-sensing and smart-processing} architecture that splits sensing and computation capabilities among tiers is proposed. Tier-1 consists of dumb sensors that only sense and transmit, while the nodes in Tier-2 do all the smart processing on Tier-1 sensor data. A low-power and low-cost solution for Tier-1 sensors has been proposed using Analog Joint Source Channel Coding~(AJSCC). An analog circuit that realizes the rectangular type of AJSCC has been proposed and realized on a Printed Circuit Board for feasibility analysis. A prototype consisting of three Tier-1 sensors (sensing temperature and humidity) communicating to a Tier-2 Cluster Head has been demonstrated to verify the proposed approach. Results show that our framework is indeed feasible to support large scale high density and persistent WSN deployment.

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Vidyasagar Sadhu, Xueyuan Zhao, Dario Pompili. 2017-01-19. Energy-efficient Analog Sensing for Large-scale, High-density Persistent Wireless Monitoring. https://doi.org/10.1109/wons.2017.7888773

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