Intelligent community intrusion detection system based on wireless sensor network and fuzzy neural network

An intelligent community intrusion detection system based on wireless sensor network and fuzzy neural network (FNN) is presented in this paper. This system is composed of ARM (Advanced RISC Machines) data acquisition nodes, wireless mesh network and control centre. The data acquisition node uses sensors to collect information and processes them by image detection algorithm, and then transmits information to control centre with wireless mesh network. When there is abnormal phenomenon, the system starts the camera and the FNN is used to recognize the face image. We construct the structure of fuzzy neural network, and adopt the Levenberg-Marquart optimizing algorithm to train fuzzy neural network, thereby enhancing the convergence rate and the recognition accuracy. With the ability of strong self-learning and nonlinear function approach of fuzzy neural network, the recognition method can truly classify the face. This system resolves the defect and improves the intelligence and alleviates worker´s working stress.