{"id":201,"date":"2024-08-08T09:48:12","date_gmt":"2024-08-08T09:48:12","guid":{"rendered":"https:\/\/test3en.nothing-creative.com\/?page_id=201"},"modified":"2026-10-20T15:03:57","modified_gmt":"2026-10-20T15:03:57","slug":"home","status":"publish","type":"page","link":"https:\/\/thinklab.lab.nycu.edu.tw\/eng\/","title":{"rendered":"Think Lab"},"content":{"rendered":"\t\t
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Development and Application of Quick-Release Flood Sensors (ECOMSNet)<\/div>
Designed for short-duration, intense rainfall events, these sensors combine edge computing, easy installation, and low maintenance costs. Within a decentralized flood warning system, they use point measurements to rapidly predict flooding across urban areas.<\/div><\/div><\/a><\/div>
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HIM model can rapidly forecast flood depths for urban areas<\/div>
The Hybrid Inundation Model (HIM) integrates cellular automata, digital elevation data, and one-dimensional Saint-Venant equations for sewer flow to enable rapid urban flood simulation.<\/div><\/div><\/a><\/div>
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Use satellite imagery to estimate inundation depths<\/div>
Satellite imagery is processed using Google Earth Engine (GEE) to identify flood extent. The team\u2019s SPM-GEE model then estimates flood depths within the identified areas.<\/div><\/div><\/a><\/div>\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t
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\n\t\t\t\n\t\t\t\tTyphoon Rainfall Prediction in Taiwan under Climate Change Scenarios: Application of a Two-Stage Bayesian Regression Model\t\t\t<\/a>\n\t\t<\/h3>\n\t\t\t\t
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Typhoons are natural disasters capable of causing severe destruction worldwide, while simultaneously serving as crucial sources of freshwater. Taking Taiwan<\/p>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/article>\n\t\t\t\t<\/div>\n\t\t\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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\n\t\t\t\n\t\t\t\tHIM model can rapidly forecast flood depths for urban areas\t\t\t<\/a>\n\t\t<\/h3>\n\t\t\t\t
\n\t\t\t\t\t\n\t\t\tJuly 30, 2024\t\t<\/span>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/article>\n\t\t\t\t
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\n\t\t\t\n\t\t\t\tFish pond early warning system for cold snaps\t\t\t<\/a>\n\t\t<\/h3>\n\t\t\t\t
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\n\t\t\t\n\t\t\t\tBayesian-based flood damage assessment\t\t\t<\/a>\n\t\t<\/h3>\n\t\t\t\t
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\n\t\t\t\n\t\t\t\tBayesian-based flood damage assessment\t\t\t<\/a>\n\t\t<\/h3>\n\t\t\t\t
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\n\t\t\t\n\t\t\t\tUse satellite imagery to estimate inundation depths\t\t\t<\/a>\n\t\t<\/h3>\n\t\t\t\t
\n\t\t\t\t\t\n\t\t\tJuly 29, 2024\t\t<\/span>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/article>\n\t\t\t\t
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\n\t\t\t\n\t\t\t\tChanges in flood risk and contingency strategies at different construction stages\t\t\t<\/a>\n\t\t<\/h3>\n\t\t\t\t
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Publication<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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1<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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A Novel Multimodal Large Language Model-Based Approach for Urban Flood Detection Using Open-Access Closed Circuit Television in Bandung, Indonesia<\/a>
November 8, 2025<\/span>\u30fb<\/span>Water, 17(18), 2739. (N\/M=40\/128=31.25%, WATER RESOURCES, 2023)<\/span><\/div><\/div><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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2<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Using Physically Estimated Temperature as Inputs to Enhance the erformance of the LSTM Model for Predicting Water Temperature in Fishponds<\/a>
November 8, 2025<\/span>\u30fb<\/span>Smart Agricultural Technology<\/span><\/div><\/div><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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3<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Combination of Large Language Models and Portable Flood Sensors for Community Flood Response: A Preliminary Study<\/a>
April 1, 2025<\/span>\u30fb<\/span>Water 2025, 17(7), 1055. (N\/M=40\/128=31.25%, WATER RESOURCES, 2023)<\/span><\/div><\/div><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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4<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\u521d\u63a2\u8c9d\u8449\u65af\u5b9a\u7406\u8a55\u4f30\u81fa\u7063\u5de5\u696d\u5340\u6d2a\u6c34\u640d\u5931\u7684\u53ef\u884c\u6027<\/a>
March 1, 2025<\/span>\u30fb<\/span>\u53f0\u7063\u6c34\u5229\uff0c\u7b2c\u4e03\u5341\u4e09\u5377 \u7b2c\u4e00\u671f\u3002(EI)<\/span><\/div><\/div><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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5<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Integration of the WRF model and IoT sensors to develop an early cold snap warning system for inland fishponds<\/a>
December 17, 2024<\/span>\u30fb<\/span>Smart Agricultural Technology, 100561. (N\/M=4\/126=3.17%, AGRONOMY, 2023)<\/span><\/div><\/div><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Development and Application of Quick-Release Flood Sensors (ECOMSNet)Designed for short-duration, intense rainfall events, these sensors combine edge computing, easy installation,<\/p>\n","protected":false},"author":3,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-201","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/thinklab.lab.nycu.edu.tw\/eng\/index.php?rest_route=\/wp\/v2\/pages\/201","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/thinklab.lab.nycu.edu.tw\/eng\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/thinklab.lab.nycu.edu.tw\/eng\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/thinklab.lab.nycu.edu.tw\/eng\/index.php?rest_route=\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/thinklab.lab.nycu.edu.tw\/eng\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=201"}],"version-history":[{"count":123,"href":"https:\/\/thinklab.lab.nycu.edu.tw\/eng\/index.php?rest_route=\/wp\/v2\/pages\/201\/revisions"}],"predecessor-version":[{"id":1437,"href":"https:\/\/thinklab.lab.nycu.edu.tw\/eng\/index.php?rest_route=\/wp\/v2\/pages\/201\/revisions\/1437"}],"wp:attachment":[{"href":"https:\/\/thinklab.lab.nycu.edu.tw\/eng\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=201"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}