Cyber to Real World Integrated Testbed for Dam Safety Management and Water Governance System
Project Introduction
In ASEAN countries, dams have helped to remedy life-threatening problems such as poverty from lack of economic development, famine resulting from drought, devastation from floods, and disease from lack of water supplies. However, dam failure risks loom due to evolving hydrological and seismic hazards induced by climate change, aging infrastructure, and varying levels of expertise in dam safety management.
To mitigate these risks, the "Cyber to Real World Integrated Testbed for Dam Safety Management and Water Governance System in ASEAN Countries" aims to bridge the gap between digital simulations and real-world implementations. Building on existing initiatives like Thailand's Dam Safety Remote Monitoring System (DS-RMS), the project seeks to enhance dam safety protocols and water governance frameworks across ASEAN nations. By leveraging advanced cyber-physical systems (CPS) technologies, the nationwide ICT testbed infrastructure and international High-Speed R&D Network Testbed will be used as a tool to connect to each country for facilitates comprehensive testing, validation, and optimization of dam safety measures.
To mitigate these risks, the "Cyber to Real World Integrated Testbed for Dam Safety Management and Water Governance System in ASEAN Countries" aims to bridge the gap between digital simulations and real-world implementations. Building on existing initiatives like Thailand's Dam Safety Remote Monitoring System (DS-RMS), the project seeks to enhance dam safety protocols and water governance frameworks across ASEAN nations. By leveraging advanced cyber-physical systems (CPS) technologies, the nationwide ICT testbed infrastructure and international High-Speed R&D Network Testbed will be used as a tool to connect to each country for facilitates comprehensive testing, validation, and optimization of dam safety measures.
Project Members
* Project Leader
Project Members | |
---|---|
Full Name | Department, Institution, Country |
Somsanouk Pathoumvanh * | National University of Laos, Laos |
Khamhou Xaphouvong | Faculty of Engineering, National University of Laos, Laos |
Khamla Nonalinsavath | Faculty of Engineering, National University of Laos, Laos |
Kanokvate Tungpimolrut | National Electronics and Computer Technology Center (NECTEC), Thailand |
Seubsuang Kachapornkul | National Electronics and Computer Technology Center (NECTEC), Thailand |
Rangsarit Vanijjirattikhan | National Electronics and Computer Technology Center (NECTEC), Thailand |
Thin Lai Lai Thien | University of Computer Studies, Yangon, Myanmar |
Nay Win Aung | University of Computer Studies, Yangon, Myanmar |
Zin May Oo | University of Computer Studies, Yangon, Myanmar |
Moe Moe Myint | University of Computer Studies, Yangon, Myanmar |
Ly Rottana | Institute of Digital Research and Innovation, CADT, Cambodia |
Cheab Sovuthy | Institute of Digital Research and Innovation, CADT, Cambodia |
Thear Sophal | Institute of Digital Research and Innovation, CADT, Cambodia |
Chea Socheat | Cambodia Academy of Digital Technology (CADT), Cambodia |
Jennifer C. Dela Cruz | Mapua University, Philippines |
Febus Reidj G. Cruz | Mapua University, Philippines |
Meo Vincent Caya | Mapua University, Philippines |
Toshiuki Miyachi | National Institute of Information and Communications Technology (NICT), Japan |
Shinsuke Miwa | National Institute of Information and Communications Technology (NICT), Japan |
Shinichi Miyakawa | National Institute of Information and Communications Technology (NICT), Japan |
- Project Information and Reviews
- Project introduction[PDF 917KB]
- 2024 Progress Report[PDF 1.66MB]
- Project meetings, field trips, tests etc. reports
- Symposium and meeting report (DOCX 2.76 MB)
- Symposium and meeting report (September 2024) (DOCX 1.8 MB)
- March 2025 Workshop and Training Report[PDF 610KB]
- Conference Reports and Presentations
- ICCAI 2025 - 2025 11th International Conference on Computing and Artificial Intelligence - Report[PDF 300KB]
- ICCAI 2025 - Schedule[PDF 1.08MB]
- ICCAI 2025 - Presentation - A Data-driven Machine Learning Approach for Reservoir Water Level Forecasting[PDF 1.05MB]