Wireless sensors and neural networks for intruders detection and classification

摘要: The problem of automating the detection and classification intruders in vast hard to reach terrains has been an active research topic over past decade. In this paper we present a new paradigm intrusion by combining sensing potential self-configuring instantly-deployable wireless sensor networks (WSN's) with reasoning capabilities artificial neural (ANN's). implemented system is referred WINIDC (Wireless Sensors Neural Networks for Intruders Detection Classification). designed detect many sizes types. It can be considered as smart economical solution addressed surveillance problem. it utilizes classify different types intruders. small, cheap nodes that are self-powered self-configuring. Traditional solutions such expensive, complex maintain. results show integrating ANNs along WSNs allow real-time accurate proposed utilized monitoring protect assets national borders.