An Improved WSN Data Integration Scheme Base on BP Neural Network

In forest fire monitoring, in order to achieve the goal of reducing a large number of invalid and redundant data in wireless sensor network, improving the convergence rate of the wireless sensor network, prolonging the life cycle of nodes, improving the accuracy of fire report, this paper proposed an improved data integration method based on BP neural network. Data generated by various sensors can be integrated on the nodes with this method, the convergence speed of BP neural network can be improved by reference of real-time processing capacity of the node, and thus the energy consumption was reduced to a great extent. The experimental results showed that the proposed method can be well applied in fire monitoring sensor network, the monitoring accuracy was improved and the energy consumption of nodes was reduced, the capacity of wireless sensor network for forest fire monitoring was increased significantly.