Lead: IIT Guwahati (IITG)
Disasters emerge from the interaction of hazards, exposure, vulnerability, and risk. Effective early warning systems (EWS) are crucial for preparedness and loss reduction...
Lead: Indian Institute of Science (IISc)
It will monitor rainfall, streamflow, and flood depth using low-cost, portable sensors such as smartphone cameras for participatory data collection...
Lead: MetaMeta Research B.V.
Each lab will integrate citizen science, horizontal learning, and serious gaming to drive socio-technical innovation for mobile and web-based Multi-Hazard Early Warning Systems (MH-EWS)...
Lead: IIT Tirupati (IIT-T)
Building on WS2 data, WS4 will develop MH-EWS algorithms and ML models for improved flood/drought forecasting...
Lead: Wageningen University & Research (WUR)
It aims to enhance expertise in flood and drought forecasting, disaster management, and policy research while promoting effective communication and use of LODESTAR findings in decision-making...