An Approach for Urban Sensing with Quality-Aware Situation Detection and Efficient Communication

Abstract

Urban Sensing employs physical-world mining to create a digital model of the physical world using a large number of sensors. Handling the large amount of data generated by sensors is costly and requires energy-saving measures for sensing and sensor data transmission. Such schemes often affect data quality and message delay. However, the detection of real-world situations using Complex Event Pro- cessing on sensor data has to be dependable and timely and requires precise data. In this position paper, we propose an approach to integrate the contradicting op- timization goals of energy-efficient wireless sensor networks and dependable situ- ation detection. It separates the system into the following tiers: First, to support energy-efficiency and allow sparse, unconnected sensor networks, we exploit the mobility of people through Delay Tolerant Networking for collecting sensor data. This frees sensor nodes from energy-expensive routing. Second, we employ Di- agnostic Simulation which provides data that is complete, precise and in time and therefore supports quality-aware situation detection.