Design And Implement Of Forest Fire Monitoring System Based On ZigBee

In order to solve the deficiency of the traditional method of forest fire monitoring, it introduced the wireless sensor network technology into the forest fire monitoring system in an effort to build the forest fire monitoring system based on ZigBee. The system used sensor network nodes to monitor real-time parameters of temperature, smoke and flame in the forest, and data was sent to the GPRS module through wireless multi-hop, then spread on the Internet using its Internet-enabled, finally transmitted to the monitoring center computer. Based on the analysis and processing of the collected data using the monitoring center computers, it determined whether a forest fire happened, and provided the foundation of taking the appropriate measures for fire departments.Research work of the system had mainly the following aspects:First, in accordance with the principle of low power consumption and the requirement of increasing the communication distance between nodes, it designed and made the hardware of sensor node with a power amplifier; Secondly, with the changes and improvement of ZigBee protocol, it gave a detailed program flow and achieved the network functions of self-organization, self-healing, periodic sleep, the smallest depth of the routing and so on; Thirdly, analyzing the path loss model of radio propagation and the specific environmental, it proposed the weighted centroid location algorithm based on RSSI, then selected three maximum-RSSI beacon nodes to process location calculation based on processing and analysis of the positioning data, so it improved the positioning accuracy. And it put forward the operating mechanism of positioning system.By experimental verification, the node basically met the low power consumption and middle-distance communication requirements, and the basic network functions had been realized, so it was feasible. The simulation and experimental results of location algorithm showed that the weighted centroid algorithm based on RSSI could be applied to the regional location.