Air quality monitoring for pervasive health

n n n n n n n n n n n n n LandSLIdE MonItorIng In thE EMILIa roMagna aPEnnInES Alberto Rosi, Matteo Berti, Nicola Bicocchi, Gabriella Castelli, Alessandro Corsini, Marco Mamei, and Franco Zambonelli Universita di Modena e Reggio Emilia Matteo Berti Universita di Bologna I taly’s Emilia Romagna Apennines are characterized by widespread landslide phenomena that pose a potential danger to villages and infrastructures. Existing monitoring technologies are coarse-grained, discontinuous, and costly. To overcome these limitations, we’ve started an interdisciplinary collaboration to study wireless sensor networks in this context. We’ve developed and deployed the first prototype in a steep landslide area near the village of Calita. The network’s infrastructure was first deployed in late 2008, and it’s been working ever since. It currently exploits 13 Crossbow Micaz motes with TinyOS software and covers a surface of approximately 500 square meters. The nodes embed accelerometer boards to capture slope movements and environmental boards to monitor ambient parameters such as temperature, pressure, humidity, and light depth. In-node processing and eventbased data delivery minimize communications and save energy. A base station delivers data to a central server every 15 minutes to support near-realtime analysis (see Figure 1). Analysis of the data collected so far proves the system’s capability to detect slope movements with high accuracy. In fact, comparisons between the sensor-network data and the data collected from the preexisting instrument sensors, such as strain gauges and inclinometers, show a good match. The wireless networks could therefore potentially act as an effective compleEnvironmental Monitoring and Task-Driven Computing