The research of event-based intelligent prediction with minimum energy consumption of wireless sensor network node state transition strategy

Abstract

Whether the state transition of wireless sensor network (WSN) nodes that are based on energy-efficient can be carried out is related to the parameters of the subsequent event's occurrence such as time, and a previous estimation of the time for the uncertain events' occurrence is necessary. In this paper, we proposed a grey multistage model with a buffer operator is utilised to get the distance between nodes, and the delivered information is predicted by PSO algorithm and is amended by Kalman filtering, then, the fuzzy reasoning based on vague set is applied to get the time value of sensor networks' uncertain events. The state transition of Wireless Sensor Networks' nodes is controlled by the time values of uncertain events and the input signal. So that the Wireless Sensor Networks' nodes can get into the optimal working mode and achieve the purpose of extending the life cycle by saving the node's energy.