Multi-View Spatiotemporal Graph Fusion AI for Sensor-Less Regional Risk Early Warning and Decision Support
Technology Introduction:
An AI early warning technology that predicts dengue risk in sensor-less urban grids by fusing ovitrap, meteorological, geographic, POI, and hydrological data through multi-view spatiotemporal graph learning. It produces citywide hotspot maps, school-neighborhood risk rankings, and resource-allocation support for public health agencies. Validated in Tainan school dengue prevention, it supports public-health early warning, cross-agency coordination, and smart-city governance.
Industrial Applications:
The technology helps health, education, and smart-city agencies generate AI risk hotspot maps, inspection lists, and resource-allocation suggestions for vector control, disinfection, school protection, and dispatch management. It reduces blind spots in sensor-sparse areas and can be extended to other urban risk-management services. It can be commercialized as a SaaS dashboard or integrated with GIS, IoT, dispatch, and school-safety systems for scalable deployment.
National Cheng Kung University
National Cheng Kung University (NCKU) envisions its campus as a place that nurtures imagination, grounded in solid academic research and high-quality learning. The university is committed to fostering urban development and global sustainability as part of its centennial mission. By breaking institutional barriers and strengthening interdisciplinary teaching and research, NCKU encourages students to recognize social issues, produce research that meets societal needs, and actively engage in solving global challenges—reflecting its responsibility as a leading university.
Contact Information
Name：Hsun-Ping Hsieh
Tel：06-275-7575 #62322
Address：No.1, Daxue Rd., East Dist., Tainan City 701, Taiwan (R.O.C.)
