The Research and Implementation of Novel Drought Forecast Model and Monitoring System Using Wireless Sensor Networks

• Main Authors: Jing-Shiuan Hua, 華瀞萱
• Other Authors: Hsu-Yang Kung
• Format: Others
• Language: zh-TW
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/93662018139770962500

碩士 === 國立屏東科技大學 === 資訊管理系 === 94 === Taiwan faces the serious challenge with an increasing frequency of drought in recent years. The main reason of drought disaster is due to the climate, e.g., the rainfall and soil moisture, it is important to utilize the state-of-the-art sensing and communication technologies to effectively monitor and forecast the drought, and notify the relevant departments for taking preventive measures against this natural disaster. This thesis proposed and developed a Drought Forecast and Alert System (DFAS) based on wireless sensor networks, which is a 4-tier system framework composed of Mobile Users (MUs), Ecology Monitoring Sensors (EMSs), Integrated Service Server (ISS), and Intelligent Drought Decision System (ID2S). DFAS combines the wireless sensor networks, embedded multimedia communications and neural network decision technologies to effectively achieve the forecast and alert of the drought. DFAS analyzes the drought level of 7th day via the proposed drought forecast model derived from the Back-Propagation Network algorithm. The mainly drought inference factors are the 30-day accumulated rainfall, daily mean temperature, and the soil moisture to improve the accuracy of drought forecast. These inference factors are detected, collected and transmitted in real-time via the Mote sensor and mobile networks. Once a region with possible drought hazard is identified, DFAS sends alerting messages to users’ appliances. System implementation results reveal that DFAS provide the drought specialists and users with complete environment sensing data and images. The proposed drought forecast model can effectively predict the occurrence of drought.