Region-specific variation
The same absolute temperature means very different things in the Hilly Region and in Interior Peninsula. Severity must be graded against a local long-period normal, not a national threshold.
AI · IoT · Climate Resilience
Heatwave intelligence for a warming India
A decision-support platform that turns long-period India Meteorological Department observations and live IoT weather-station telemetry into region-wise heatwave forecasts, hotspot maps and stakeholder-ready early warnings.
Current regional outlook
Forecast maximum temperature, seven IMD homogeneous regions
Normal
Caution
Heat Wave
Severe Heat Wave
Regions monitored
7
IMD homogeneous regions
Active heat alerts
4
Heat wave grade or above
Hotspots flagged
15
Getis-Ord Gi* clusters
AWS nodes deployed
8
Mumbai & Pune corridor
The problem
Heat is now the most under-warned extreme in India
Heatwave frequency, intensity and duration have all risen across the subcontinent, yet severity varies sharply between regions because of local weather characteristics and environmental factors. Coarse, nationwide bulletins do not reach the district officer, the farmer or the hospital duty roster in a form they can act on.
Sparse ground truth
Gridded model output needs validation against real observations. Without dense local measurement, a forecast cannot be checked before an advisory is issued on it.
Last-mile translation
A departure of +5.5 °C is meaningless to a citizen. Technical forecasts have to be rewritten for each audience, quickly, and in a form that survives review.
Solution approach
Five interlocking phases, from raw GRD files to a district advisory
The platform implements the conceptual schema of Use Case KJS-CES-01 end to end.
PHASE I
Data acquisition
IMD gridded maximum-temperature GRD archives are ingested, quality-checked, cleaned and stored region-wise.
PHASE II
AI analytics
Spatio-temporal models forecast Tmax, predict heatwave onset, identify hotspots and classify severity.
PHASE III
IoT monitoring
Automated Weather Stations stream localized temperature, humidity and wind observations continuously.
PHASE IV
Validation
Ground observations are matched against model output to score and correct region-wise forecasts.
PHASE V
Advisory & warning
Dashboards visualise the picture and an LLM drafts audience-specific advisories for expert review.
Who it serves
Built around the people who have to act on the warning
Disaster management
State authorities get lead time, hotspot maps and exposed-population estimates to pre-position relief.
Municipal corporations
Ward-level triggers for opening cooling centres, water kiosks and revised labour timings.
Health departments
Advance notice to staff heat-stroke corners and to begin heat-illness surveillance reporting.
Agriculture & citizens
Crop and livestock protection guidance, and plain-language safety advice in the local idiom.
See the current heatwave picture
The watch dashboard carries the live region-wise severity grading, the hotspot map and the exposed-population estimate.