Development of an AIoT-Based Early Flash-Flood Warning System for Smart Rural Disaster Resilience
| dc.contributor.author | Wiangnak, Visit | |
| dc.contributor.author | Wiboonrat, Montri | |
| dc.contributor.author | Duangsuwan, Sarun | |
| dc.date.accessioned | 2026-08-06T10:55:38Z | |
| dc.date.available | 2026-08-06T10:55:38Z | |
| dc.date.issued | 2026-06-01 | |
| dc.description.abstract | This paper presents the development of an AIoT-based early flash-flood warning system to enhance disaster resilience in smart rural communities. The framework integrates multi-source hydrological sensors, AI-enabled edge–cloud computing, and a mobile alert application to provide real-time monitoring and short-term flood forecasting, and includes an intelligent hybrid model combines YOLOv10 for visual water-level detection from CCTV imagery with a long short-term memory (LSTM) network for hydrological time-series prediction. The system was deployed and evaluated at two sites in Thailand: the Ban Luang station in Chiang Mai and the Chumkho station in Chumphon. The experimental results show near-perfect detection performance by YOLOv10, with precision and mAP@0.5 exceeding 0.99 across varying water-level conditions. The LSTM model achieved high forecasting accuracy, with an R<sup>2</sup> of 0.987 at Ban Luang and 0.781 at Chumkho, reflecting site-specific hydrodynamic complexity. The results confirm that integrating AIoT-based visual sensing with data-driven forecasting significantly improves the reliability, responsiveness, and robustness of early flash-flood warning systems in rural environments. | |
| dc.identifier.citation | Sensors, 26(11), 2026 | |
| dc.identifier.doi | 10.3390/s26113512 | |
| dc.identifier.issn | 14248220 | |
| dc.identifier.other | 2-s2.0-105041430474 | |
| dc.identifier.uri | https://dspace.kmitl.ac.th/handle/123456789/18131 | |
| dc.source | Sensors | |
| dc.subject | AIoT | |
| dc.subject | early flash-flood warning system | |
| dc.subject | rural disaster resilience | |
| dc.subject | smart environment | |
| dc.title | Development of an AIoT-Based Early Flash-Flood Warning System for Smart Rural Disaster Resilience | |
| dc.type | Article |