An Automatic Diagnosis and Warning Scheme for the Ecological Monitoring System for the Bactrocera dorsalis (Hendel) using Self-Organizing Map

• Main Authors: Min-Sheng Liao, 廖敏勝
• Other Authors: 廖國基
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/51665101753796785389

碩士 === 國立臺灣大學 === 生物產業機電工程學研究所 === 99 === Recently, wireless sensor networks (WSNs) technologies have been rapidly developed. WSNs have been widely utilized in a variety of commercial and industrial applications. If a back-end monitoring technology accompany with WSNs, it can be used to detect the specific events of WSNs. For example, with unusually high or low temperature and humidity, the back-end monitoring system can aim at the specific events and prepare for the follow-up operations of environmental control and emergency notification. However, the causation of the specific events may also be resulted from sensor calibration error or sensor failure. In order to avoid the false positives of the monitoring system, it must establish a mechanism of autonomous detection to prevent similar situations. This work instanced an oriental fruit fly (Bactrocera dorsalis) ecological monitoring network, and it designed a real-time monitoring system. This system can send warning messages to the correspondents when the pest surged. In addition, when a sensor reading error occurs, this system can accurately classified as a fault event, and notify the correspondents to conduct system maintenance. The oriental fruit fly is the major pest that attacks fruit in Taiwan. In the past, the monitor techniques mostly depended on manual measurement. Due to limited budgets on manpower, manual measurements cannot acquire much environmental data at the same time, thereby losing the immediateness of subsequent data analysis, so it is almost impossible to execute appropriate pest control in the right time at the right place. In order to replace previous manual measurements, this work combined GSM technologies with WSN technologies to develop an automated real-time monitoring system which can measure environmental parameters for cultivated land. The mechanism of autonomous detection used self-organizing map to detect the parameters of specific events. This work achieves three primary goals: 1) the sensors operate normally; 2) the sensors detect the infestation of the oriental fruit; and 3) the system detects unusual sensor readings. Two monitoring systems of the oriental fruit fly have been actually deployed in two orange orchards at Yuanshan, Yilan, on July 2 and Sept. 8, 2010, respectively. The systems can monitor the oriental fruit fly in the orchards and use self-organizing map to establish classification models for four seasons. The models will classify the readings based on three primary goals set by this work. The experimental results presented that the efficiency of classification models is excellent, and it can help the monitoring system identify whether an error in the monitoring data occurs to achieve agricultural automation.