INTEGRATION OF AI IN NATIONAL DISASTER MANAGEMENT

1. At a Glance

2. Why in the News

3. Background & Evolution

4. Core Static Facts

5. Multi-Dimensional Analysis

Scientific/Technological - AI/ML enables predictive modelling of cyclone tracks, urban floods, heatwaves and avalanches beyond classical NWP horizons [S2]. - Cell Broadcast delivers location-based push alerts to all phones in a cell without app/SIM dependency [S2].

Legal/Constitutional - Disaster Management is governed under Concurrent List via the DM Act 2005; UDMAs add a third tier below SDMA/DDMA [S1][S3]. - Section 41A is an enabling (not mandatory) provision — states may constitute UDMAs [S1].

Administrative/Federalism - City-specific authority addresses cross-district urban agglomeration risks [S1]. - Exclusion of Delhi/Chandigarh reflects existing UT-specific governance arrangements [S1].

Social/Environmental - Urban Plans must specifically tackle flooding and heatwaves — climate-adaptation mainstreamed into city planning [S1]. - AI-based early warning narrows the gender/poverty gap in disaster mortality by enabling last-mile alerts [S2].

Ethical/Governance - AI in alerts raises concerns over data privacy, algorithmic bias in risk prioritisation, and accountability for false negatives.

6. Recent Developments (last 12–18 months)

7. Prelims Hooks

8. Mains Relevance

9. Related Topics to Study Next

10. Common Errors / Trap Areas

11. Sources