No abstract

Wireless sensor networks (WSN) provide an inexpensive and convenient way to monitor physical environments. Integrating the context-aware capability of WSN into surveillance systems is an attractive direction. We thus propose an integrated mobile surveillance and wireless sensor (iMouse) system, which consists of a large number of inexpensive static sensors and a small number of more expensive mobile sensors. The former is to monitor the environment, while the latter can move to certain locations and takes more advanced actions. The iMouse system is a mobile, context-aware surveillance system. We demonstrate our current prototyping for home security applications. Besides, we analyze its event detection delay under an any-sensor-detection model.

A wireless sensor network (WSN) consists of many tiny and low-power devices deployed in a sensing field. One of the major tasks of a WSN is to monitor the surrounding environment and to detect events occurring in the sensing field. Given an event appearing in a WSN, the event detection latency is to model the time that it takes for the WSN to be aware of the event.In this work, we analyze the latency using a probabilistic approach under an any-sensor-detection and a k-sensor-detection models, where k > 1 is an integer. Such an analysis can be used as an index to evaluate a WSN's coverage and thus can help guide the deployment of a WSN. We also develop simulations to verify our analytical results.