Energy efficient gas emission monitoring systems using wireless sensor networks

Abstract

Use of Wireless Sensor Networks(WSNs) in environmental gas emission monitoring system can provide inexpensive, portable, and easily accessible system. In most cases naive use of WSNs in gas emission monitoring will fail to provide long-term and cost-effective system due to very high power requirement of most gas sensors. In this work, we support this claim by a quantitative analysis of the main operational energy costs of some popular gas sensors, radios, and sensor motes use in WSN-based gas monitoring systems. In light of the importance of sensing level energy costs for power hungry gas sensors, we consider compressed sensing as a potential approach to minimize sensing energy costs in Wireless Sensor Networks based gas emission monitoring system. Numerical experiments investigating the effectiveness of compressed sensing using real datasets show its potential for minimizing sensing and overall energy costs in Wireless Sensor Networks based gas emission monitoring system. Results shown that, for gas monitoring, compressed sensing can provide greater energy efficiency than transform coding, and model based adaptive sensing in Wireless Sensor Networks.