From Nepal to India: How AI Is Transforming Disaster Management
Context
Recent disasters in Nepal and India have highlighted the growing role of Artificial Intelligence in disaster management. AI enabled systems are being used for crowdsourced information, damage assessment, weather forecasting, early warning, rescue planning and post disaster relief. One of the major advantages of AI is its ability to analyse large and diverse datasets rapidly, enabling authorities to make faster and more informed decisions during emergencies.
Key Highlights
- AI-assisted search and rescue:
During a disaster in Nepal, an AI enabled web platform reportedly combined crowdsourced information with official data to identify missing people and support rescue operations. AI enabled drones were also used to detect human like thermal signatures beneath debris. - Applications in India:
In India, governments, private organisations, satellite data providers and technology companies are increasingly using AI for weather forecasting, hazard mapping, satellite imagery analysis and disaster preparedness. - Improved weather forecasting:
AI based weather models can analyse large datasets to identify atmospheric patterns and produce more localised and timely forecasts. Google’s Flood Hub is one example of an AI based system used for flood prediction and related advisories. - Strengthening emergency response:
AI can analyse information collected through smartphones, drones, social media, sensors and other sources to identify stranded communities, damaged infrastructure and potentially accessible routes for rescue teams. - Post-disaster management:
AI-enabled tools can assist in identifying isolated settlements, assessing road conditions, locating suitable helicopter landing areas and helping authorities prioritise the distribution of food, medicines and other relief supplies.
Way Forward
India should develop AI enabled and interoperable disaster management platforms that can integrate information from multiple sources. At the same time, their deployment should include human oversight, reliable datasets, privacy protection, local language accessibility and equitable access to technology. This can help ensure that AI complements existing disaster management institutions while improving preparedness, response and recovery.