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

## TL;DR

This paper proposes an energy-efficient wireless sensor network architecture that separates sensing and processing, utilizing low-power analog circuits for sensing, enabling scalable and persistent environmental monitoring.

## Contribution

It introduces a novel dumb-sensing and smart-processing architecture with an analog joint source channel coding circuit for low-power sensors, demonstrated through a prototype.

## Key findings

- Feasible to support large-scale high-density deployments
- Analog sensing circuit reduces power consumption
- Prototype verifies system effectiveness

## 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.