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.