WSN and ANP Used on Slope Disaster Prediction and Monitoring System: Design and Implementation
碩士 === 國立屏東科技大學 === 資訊管理系所 === 96 === In Taiwan, there are usually large-scale debrisflows and landslides in the typhoon season or torrential rain falls. As the rapid progress of wireless sensor networks (WSN) and mobile communication technology, it is the hot issue that using the-state-of-the-art t...
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ndltd-TW-096NPUS53960262016-12-22T04:12:08Z http://ndltd.ncl.edu.tw/handle/11302317059418245748 WSN and ANP Used on Slope Disaster Prediction and Monitoring System: Design and Implementation 無線感測網路結合分析網路程序法應用於邊坡災害預測與監控系統之設計與實作 Li-Chia Kuo 郭俐佳 碩士 國立屏東科技大學 資訊管理系所 96 In Taiwan, there are usually large-scale debrisflows and landslides in the typhoon season or torrential rain falls. As the rapid progress of wireless sensor networks (WSN) and mobile communication technology, it is the hot issue that using the-state-of-the-art technology to build a reliably disaster prediction model and monitor and collect environment variation information. This paper integrates WSN and Analytic Network Process (ANP) method to evaluate the weight of disaster factors, which is determined using the consistency index of hillslope pairwise comparison. The weight estimation and classly of disaster factors and based on the K-means model to build the hillslope prediction model. Base on the proposed disaster prediction model, we design and implement the “Portrait-based Disaster Alerting System, (PDAS)”. PDAS is four-tier architecture composed of Mobile User Site, Hillslopes Monitoring Sensor Site, Integrated Service Server, and Intelligent Hillslopes Decision System. Mobile User (MU) Site uses the handheld devices to transmit and receive multimedia information about hillslop disasters via the mobile networks. Hillslope Monitoring Sensor (HMS) Site includes the Hillslope Monitoring Engine, network camera, and sensors to collect environment information. Integrated Service Server (ISS) is composed of six intelligent agents to process the received environment information. Intelligent Hillslope Decision System (IHDS) is responsible to determine the probability of hillslope disaster occurrence based on the information from sensors. The hillslope disaster prediction model defines seven disaster factors, which include soil hydrous, rainfall, NDVI, light, displacement, and gradient, to evaluate and analysis the probability of hillslope disaster. The PDAS uses Web-GISto display the environment information visualized. The system evaluation results reveal the proposed prediction model achieves more accuracy disaster determination than the traditional method. Hsu-Yang Kung 龔旭陽 2008 學位論文 ; thesis 130 zh-TW |
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碩士 === 國立屏東科技大學 === 資訊管理系所 === 96 === In Taiwan, there are usually large-scale debrisflows and landslides in the typhoon season or torrential rain falls. As the rapid progress of wireless sensor networks (WSN) and mobile communication technology, it is the hot issue that using the-state-of-the-art technology to build a reliably disaster prediction model and monitor and collect environment variation information. This paper integrates WSN and Analytic Network Process (ANP) method to evaluate the weight of disaster factors, which is determined using the consistency index of hillslope pairwise comparison. The weight estimation and classly of disaster factors and based on the K-means model to build the hillslope prediction model. Base on the proposed disaster prediction model, we design and implement the “Portrait-based Disaster Alerting System, (PDAS)”. PDAS is four-tier architecture composed of Mobile User Site, Hillslopes Monitoring Sensor Site, Integrated Service Server, and Intelligent Hillslopes Decision System. Mobile User (MU) Site uses the handheld devices to transmit and receive multimedia information about hillslop disasters via the mobile networks. Hillslope Monitoring Sensor (HMS) Site includes the Hillslope Monitoring Engine, network camera, and sensors to collect environment information. Integrated Service Server (ISS) is composed of six intelligent agents to process the received environment information. Intelligent Hillslope Decision System (IHDS) is responsible to determine the probability of hillslope disaster occurrence based on the information from sensors. The hillslope disaster prediction model defines seven disaster factors, which include soil hydrous, rainfall, NDVI, light, displacement, and gradient, to evaluate and analysis the probability of hillslope disaster. The PDAS uses Web-GISto display the environment information visualized. The system evaluation results reveal the proposed prediction model achieves more accuracy disaster determination than the traditional method.
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author2 |
Hsu-Yang Kung |
author_facet |
Hsu-Yang Kung Li-Chia Kuo 郭俐佳 |
author |
Li-Chia Kuo 郭俐佳 |
spellingShingle |
Li-Chia Kuo 郭俐佳 WSN and ANP Used on Slope Disaster Prediction and Monitoring System: Design and Implementation |
author_sort |
Li-Chia Kuo |
title |
WSN and ANP Used on Slope Disaster Prediction and Monitoring System: Design and Implementation |
title_short |
WSN and ANP Used on Slope Disaster Prediction and Monitoring System: Design and Implementation |
title_full |
WSN and ANP Used on Slope Disaster Prediction and Monitoring System: Design and Implementation |
title_fullStr |
WSN and ANP Used on Slope Disaster Prediction and Monitoring System: Design and Implementation |
title_full_unstemmed |
WSN and ANP Used on Slope Disaster Prediction and Monitoring System: Design and Implementation |
title_sort |
wsn and anp used on slope disaster prediction and monitoring system: design and implementation |
publishDate |
2008 |
url |
http://ndltd.ncl.edu.tw/handle/11302317059418245748 |
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