Wireless Sensor Networks for Distributed Chemical Sensing: Addressing Power Consumption Limits With On-Board Intelligence

Abstract

Chemicals detection and quantification is extremely important for ensuring safety and security in multiple application domains like smart environments, building automation, etc. Characteristics of chemical signal propagation make single point of measure approach mostly inefficient. Distributed chemical sensing with wireless platforms may be the key for reconstructing chemical images of sensed environment but its development is currently hampered by technological limits on solid-state sensors power management. We present the implementation of power saving sensor censoring strategies on a novel wireless electronic nose platform specifically designed for cooperative chemical sensing and based on TinyOS. An on-board sensor fusion component complements its software architecture with the capability of locally estimate air quality and chemicals concentrations. Each node is hence capable to decide the informative content of sampled data extending the operative lifespan of the entire network. Actual power savings are modeled and estimated with a measurement approach in experimental scenarios.