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