Research On Energy Acquisition Wireless Sensor Network Monitoring Coverage And Transmission Energy Efficiency

Continuous and effective regional monitoring of the water environment is of great significance to water environmental protection.Currently,wireless sensor networks have been widely used in monitoring fields such as mines,bridges,and water environment due to their low power consumption and low cost technical advantages.However,traditional wireless sensor networks are usually powered by batteries.Due to the limited battery life,in remote water environment areas with insufficient power supply facilities,node deaths are likely to occur during monitoring and communication,resulting in interruption of wireless sensor network communication Or failure and other issues.In response to the above-mentioned problems of water environment monitoring by traditional wireless sensor networks,in recent years,the emergence of energy-harvesting wireless sensor networks has provided a solution for continuous and effective water environment monitoring.The network monitoring nodes from the external environment(such as Solar energy,wind energy)obtain energy,and achieve continuous monitoring and transmission of water environment through energy optimization management,which provides technical support for improving the performance of water environment monitoring.Therefore,this paper takes water environment monitoring as the research background,and takes the water environment monitoring coverage and transmission of the energy acquisition sensor network as the research object.The focus is on the solar energy prediction problem in the water environment monitoring area in the wireless sensor network,combined with weather,environment and other factors.Solar energy prediction accuracy;on this basis,research the target coverage problem of wireless sensor networks,and schedule the coverage of sensor nodes to maximize target coverage;in addition,for the effectiveness of energy acquisition wireless sensor network information transmission,the research passed Improve the routing protocol to improve the transmission energy efficiency performance of the energy harvesting wireless sensor network,and provide a theoretical reference for improving the coverage and transmission utility.The specific research content is as follows:(1)Solar energy forecast problems in the monitoring area.In the wireless sensor network area,due to the variability of the environment,solar energy is unstable,and the node's scheduling of battery energy depends on the arrival of solar energy.In this context,the BP neural network algorithm is used to predict the solar energy in themonitoring area based on the illumination,temperature,and solar diffuse reflection intensity of each time period.Finally,verify the accuracy with the solar energy information in the monitoring area.(2)Target coverage of wireless sensor network.When the directional sensor covers the target,because of the sensor's own characteristics,only one coverage direction can be activated at each working direction.In this context,the problem of optimal coverage utility of the sensor network for target monitoring is studied.The purpose is to study the effective monitoring of targets in the entire monitoring area to avoid repeated coverage of the target by nodes and cause waste of sensor nodes.Based on reinforcement learning Algorithm node scheduling coverage method.Finally verify the effectiveness of the algorithm(3)Optimization of wireless routing protocols.In information transmission in wireless sensor networks,the optimization of routing protocols is a key point to improve the life of wireless sensor networks.An improved LEACH protocol optimization method based on clustering k-means algorithm is proposed.The method classifies sensor nodes according to distance factors,and competes for cluster heads in the cluster formed by nodes,which effectively avoids the formation of uneven distribution of cluster heads and causes node transmission information The problem of excessive consumption of node energy in the process,simulation results show that the proposed method effectively improves the network life.