Research On Routing And Positioning Algorithms For Forest Fire Monitoring

Forest fire monitoring technology is of great importance to the prevention and rescue of forest fires.However,the current forest fire monitoring technology is constrained by various factors,and the monitoring effect is not ideal for the protection of forest resources.With the continuous popularization and development of Wireless Sensor Networks(WSN)technology,WSN-based forest fire monitoring technology has become a hot spot for research.To address the problems of high node energy consumption,high positioning cost and low positioning accuracy in the routing and positioning algorithms for forest fire monitoring,two improved algorithms and a forest fire monitoring interface are designed in this paper,and the specific work is as follows:(1)Design an improved routing algorithm based on partitioned hierarchical clustering.The algorithm firstly,through partitioned hierarchical clustering,makes the cluster head nodes evenly distributed in the monitoring area,and balances the overall network energy consumption;then,when screening the optimal cluster head,the remaining energy of the node,the distance between the two cluster heads and the energy consumption of the cluster group were combined to evaluate the cluster heads of each interval to determine the optimal cluster heads;finally,the data is uploaded through multiple hops.The experimental results show that the average residual energy of the improved algorithm is 26 times and 1.8 times higher than that of the original LEACH algorithm and JC-LEACH algorithm at 1200 rounds of algorithm iteration,so the algorithm can effectively reduce the network energy consumption and extend the whole network life cycle.(2)Design an RSSI prime locating algorithm based on hybrid genetic particle swarm algorithm optimization.The algorithm uses the wireless signal fading model to obtain the inter-node distance,which is used to find three neighboring anchor nodes around the unknown node and then constructs a suitable fitness function.In solving the optimal solution,a genetic algorithm is incorporated to generate a high-quality population of offspring through crossover variation,while a chaotic algorithm is used to enhance the search traversal to improve the situation where the particle swarm algorithm falls into local optimality,and to make the optimal solution of better quality.The experimental results show that under the condition that the ratio of anchor nodes is 0.3 and the communication radius is 210 m,the average localization error of the improved algorithm is reduced by 33.6%,22.4% and 12.4%compared with the traditional placental localization algorithm,RSSI-weighted placental localization algorithm and PSO-RSSI localization algorithm respectively,so the improved algorithm designed in this paper has higher localization accuracy.(3)Design a human-computer interaction interface with a simple interface and easy operation.The interface allows the user to intuitively see the real-time parameter information of the forest environment,such as the working status of nodes,alarm node location information and real-time monitoring data so that it can better complete the task of forest fire monitoring.