Fault tolerant complex event detection in WSNs: A case study in structural health monitoring

Reliably detecting event in the presence of faulty nodes, particularly nodes with faulty readings is a fundamental task in wireless sensor networks (WSNs). Existing fault-tolerant event detection schemes usually 'mask' the effect of faulty readings through high-level fusion techniques. However, in some applications such as structural health monitoring (SHM) and volcano monitoring, detecting the events of interest requires low-level data collaboration from multiple sensors. This implies that the effect of faulty readings cannot be masked once they are involved into event detection. Nodes with faulty readings must be firstly detected and removed from the system. Unfortunately, most existing techniques to detect faulty nodes can only take boolean or scalar data as input while in these applications, data generated from each sensor is a sequence of dynamic data. In this paper, we address these issues using an example of SHM. Detecting event in SHM (i.e. structural damage) requires low level collaboration from multiple sensors, and each sensor generates a sequence of dynamic vibrational data. We proposed a fault-tolerant event detection scheme in SHM called FTED. In FTED, three novel techniques are proposed: (1) distributed extraction of features for faulty node detection, (2) iterative faulty node detection (I-FUND), and (3) distributed event detection. In particular, I-FUND takes vector as input and can even handle the 'element mismatch problem' where comparable elements in vectors are located at unknown different positions. The effectiveness of FTED is demonstrated through both simulations and real experiments.