The Design And Implementation Of Energy-harvesting Wireless Sensor Network

With the development of low-power chips and embedded systems, the wireless sensor network(WSN) gradually enters the field of agricultural production. Wireless sensor network has a great advantage acquisition and transmission of the agriculture information. It provides real-time information with high accuracy. It adapts to a variety of harsh environment with low maintenance.Oriented to the demand of agricultural environmental monitoring, this thesis designed a remote environment monitoring system based on embedded system. The system monitors soil temperature and humidity, and light intensity on a long term unattended circumstance. It can retrieve the monitoring data without establishing a long distance wired or wireless link at the first place. Moreover, the energy harvesting module collects solar energy and converts it into electricity, to power the sensor network itself.The system consists of three types of nodes: data collecting node, the sink node, and the mobile commuting node. A number of data collecting nodes are deployed in the monitoring region, responsible for collecting environmental data, and sending the data to the sink node; the sink node stores the data it received; the mobile commuting node retrieves the data from the sink node and takes it back to the monitoring terminal at the base. The nodes communicates with each other using Zigbee technology, the mobile commuting node and the monitoring terminal is connected by serial port.In order to extend the life span of the system, this thesis studied the solar energy harvesting technology and proposed an integrated energy harvesting scheme and a combined energy harvesting scheme. Then this thesis implemented and tested the integrated energy harvesting scheme.Based on the deep analysis of the classic wireless sensor network routing protocol(LEACH), this thesis proposed an improved routing protocol which oriented the characteristics of energy harvesting wireless sensor network. The improved protocol calculates the optimal number of cluster heads in the network, and clusters the nodes using the K-means clustering algorithm. By this way, the number of cluster head and the rationality of their distribution can be ensured. The improved protocol was tested using Matlab simulation.