Detecting changes in signals and systems—a survey
Automatica (Journal of IFAC)
Detection of abrupt changes: theory and application
Detection of abrupt changes: theory and application
Distributed Detection and Data Fusion
Distributed Detection and Data Fusion
Power-Efficient Direct-Voting Assurance for Data Fusion in Wireless Sensor Networks
IEEE Transactions on Computers
Data versus decision fusion for distributed classification in sensor networks
MILCOM'03 Proceedings of the 2003 IEEE conference on Military communications - Volume I
Asymptotic results for decentralized detection in power constrained wireless sensor networks
IEEE Journal on Selected Areas in Communications
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Wireless sensor networks (WSN) are composed of a large number of sensor nodes and usually used to monitor a region of interest. The sensor nodes are very prone to damage due to low-cost design and random deployment. Additionally, faulty nodes may degrade the performance of the distributed hypothesis testing. This work addresses fault isolation in WSN where the fusion center attempts to identify faulty nodes through temporal sequences of received local decisions. Owing to the processor, memory, and power constraints in embedded systems, the employed method should be as simple as possible. Therefore, the primary goal of this investigation is to design a low-complexity sensor fault detection scheme, which can detect most sensor faults by using the majority voting technique. The simulation results show the proposed approach is effective in terms of identifying faulty members in a distributed sensor network.