Fault tolerant wireless sensor network using case based reasoning with semantic tracking
CIT'11 Proceedings of the 5th WSEAS international conference on Communications and information technology
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This paper presents some approaches on the new applications in fault detection and diagnosis emerged from three powerful concepts: theory of distributed parameter systems, applied to large and complex physical processes; artificial intelligence, with its tools fuzzy logic and neural networks; and the intelligent wireless ad-hoc sensor networks. Even with their limited resources of energy, memory, computational power and bandwidth sensor networks have large and successful applications in the real world. They may be placed in the areas of distributed parameter systems and they may be seen as distributed measuring sensors for the physical variables of distributed parameter systems. Fault detection and diagnosis in distributed parameter systems became more easily and more performing using these concepts. The paper presents some applications in fault detection and diagnosis based on fuzzy logic and artificial neural networks. Fuzzy logic allows the treatment of physical variables by human reasoning on operator knowledge, with fuzzy concepts of membership functions. Neural networks allow treatment of large and complex systems with many variables by learning and extrapolation. Using sensor networks multivariable estimation techniques may be applied in distributed parameter systems.