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Development of Intelligence Response Robot, 2019.01.30-Present
(MOEAWRA1080111, MOEAWRA1090315, MOEAWRA1100060, MOEAWRA1110280) WRA AI robot Diana is a disaster management decision support system developed for the Water Resource Agency (WRA) in the form of a chatbot, dedicated to serving high-level decision makers and officers to grasp the situation of water-related disasters. By 4 Nov. 2020, over 43 thousand users have added WRA AI robot Diana to their contacts, including about 250 decision makers and staff of the WRA. The overall number of interactions within WRA AI robot Diana and the users for retrieving disaster-related data is over 180 thousand. WRA AI robot Diana provides 5 topics of information: weather, preparation, response, recovery, and others. The significant utilities include: warning information notification, information design and retrieval, and fuzzy search. |
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Mining Intelligent Question-Answering Bot, 2019.10.19-present (1080901W)
Mine’s Light is a disaster management decision support system developed for the Bureau of Mine in the form of a chatbot. It is dedicated to serving the decision makers of the bureau and the staff of the safety department. Mine’s Light provides 4 topics of information: weather, disaster information, laws and documents, and others. The significant utilities include warning information notification and information design and retrieval.
Mine’s Light is a disaster management decision support system developed for the Bureau of Mine in the form of a chatbot. It is dedicated to serving the decision makers of the bureau and the staff of the safety department. Mine’s Light provides 4 topics of information: weather, disaster information, laws and documents, and others. The significant utilities include warning information notification and information design and retrieval.
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Digital Learning Project for Resolving Campus Disaster Prevention Issues
by Assimilating Problem-oriented and STEAM Teaching Method, 2022.08.18-present This project intends to implement the goal of disaster prevention education policy, offering students exploration and solutions on campus disaster prevention and assimilating PBL and STEAM into digital learning to conform to the 12 years of national fundamental education syllabus issue through developing digital teaching material modules that are suitable for each learning stage to assist teachers conducting course material development and establish practical digital disaster prevention education models, to cultivate students' ability to solve campus problems and present improvement strategies. NTUST and Tatung University teams co-develop digital disaster prevention teaching e-books for teachers to allow teachers to use the e-books to teach students disaster prevention knowledge; digital teaching material can also enhance students' relevant knowledge regarding disaster prevention. Besides editing extended teaching material based on the syllabus from the Ministry of Education, we also visit the advisory group of each school to acquire more material that fits the needs of field learning. The interactive e-book we develop can provide interaction and discussion between teachers and students in class. With the implementation of integrated disaster prevention resource technology, we will create an environment for co-creating action learning digital resources. |
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High-Availability Dialogue System for Disaster Decision Support and Management, 2019.01.01-12.31 (MOST 108-2119-M-011-002)
The project aims to develop a Decision Support Dialogue System for Disaster Management with High Availability. The proposed system allows the decision makers to instantly access the required information in the form of natural language for eliminating the inefficiencies and difficulties. The disaster prevention response information can thus be improved, and the efficiency of decision making can also be compared. Also, the system establishes an exchange data monitor and a system maintenance mechanism to ensure the high availability of the proposed system.
This project also developed:
(1) Formosa: an open-source visualization package, cooperates warning information with the administrative division boundary data and generates figures marking out the alert areas with different colors. Formosa was developed with Python and is licensed under the MIT license for public use.
(2) T-search: a historical typhoon search engine based on track similarity developed for decision makers to predict the damage that will be induced by upcoming typhoons. T-search utilizes the RSMC Tokyo best track data and provides the function of importing current typhoon forecasts of several meteorological institutions all over the world. The system reduces the time needed to manually compare tracks and find historical records.
The project aims to develop a Decision Support Dialogue System for Disaster Management with High Availability. The proposed system allows the decision makers to instantly access the required information in the form of natural language for eliminating the inefficiencies and difficulties. The disaster prevention response information can thus be improved, and the efficiency of decision making can also be compared. Also, the system establishes an exchange data monitor and a system maintenance mechanism to ensure the high availability of the proposed system.
This project also developed:
(1) Formosa: an open-source visualization package, cooperates warning information with the administrative division boundary data and generates figures marking out the alert areas with different colors. Formosa was developed with Python and is licensed under the MIT license for public use.
(2) T-search: a historical typhoon search engine based on track similarity developed for decision makers to predict the damage that will be induced by upcoming typhoons. T-search utilizes the RSMC Tokyo best track data and provides the function of importing current typhoon forecasts of several meteorological institutions all over the world. The system reduces the time needed to manually compare tracks and find historical records.
Conversation-based Decision Support System, 2018.01.01-12.31 (MOST 107-2119-M-002-017, MOST 107-2119-M-011-002)
This project aims to develop a Conversation-based Decision Support System (C-DSS). This project was worked with LINE and CoolBe Co., Ltd. for platform development and optimization. For the project result testing, this project worked with Center for Weather and Climate Disaster Research at National Taiwan University and the Water Resource Agency Disaster Emergency Response Service of Ministry of Economic Affairs to conduct the field testing during emergency responses in flood season, typhoon and heavy rain. The validation shows that the method can analyze and process the user's questions with a success rate of about 70%. This perfected the C-DSS and promote the implementation effectively to the actual operation mechanism, allowing the upper-level decision making officers at the Water Resource Agency to use the system in supporting their disaster prevention decision making.
＊發明專利：蔡孟涵、詹皓詠，『環境資訊問答系統與方法』，中華民國發明專利證書號：I688873，公告日：2020年3月21日。
＊研發原型概念獲得臺灣防災產業協會106年度防災科技應用技術優質獎佳作：防災智慧聊天機器人。
This project aims to develop a Conversation-based Decision Support System (C-DSS). This project was worked with LINE and CoolBe Co., Ltd. for platform development and optimization. For the project result testing, this project worked with Center for Weather and Climate Disaster Research at National Taiwan University and the Water Resource Agency Disaster Emergency Response Service of Ministry of Economic Affairs to conduct the field testing during emergency responses in flood season, typhoon and heavy rain. The validation shows that the method can analyze and process the user's questions with a success rate of about 70%. This perfected the C-DSS and promote the implementation effectively to the actual operation mechanism, allowing the upper-level decision making officers at the Water Resource Agency to use the system in supporting their disaster prevention decision making.
＊發明專利：蔡孟涵、詹皓詠，『環境資訊問答系統與方法』，中華民國發明專利證書號：I688873，公告日：2020年3月21日。
＊研發原型概念獲得臺灣防災產業協會106年度防災科技應用技術優質獎佳作：防災智慧聊天機器人。