An AI-enabled geospatial web system that uses satellite imagery and thermal data to classify industrial fires and show them on a map.
National Technical Research Organisation (NTRO) · Software
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Decomposed from what the description asks for. Nothing added.
Data Integration Module
Combines NASA FIRMS thermal anomaly data, land-cover information, and industrial databases.
AI Classification Engine
Automatically distinguishes industrial fires from forest fires, agricultural burning, and mining activity.
GIS Mapping Interface
Visualizes the classified thermal sources and fires as an overlay on standard maps.
Storage and Monitoring System
Stores processed data and supports ongoing monitoring of persistent thermal sources.
Both columns are read off the brief's own wording. Nothing here is inferred from the ministry's name.
The jury will check if your system can correctly separate industrial fires from natural fires using the required data sources, and whether your GIS interface displays the output clearly as a map overlay.
A jury can still ask about these. Decide them deliberately rather than by accident.
Generated from the brief's own wording and the competition's published rules, never from a guess about what this ministry prefers.
Specific industrial database schemas to use?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Exact satellite imagery sources required beyond NASA FIRMS?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Performance or accuracy targets for the AI classification?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Has any part of this been shown at a previous event, hackathon or college project?
The guidelines are explicit: your solution must not have appeared in any previous event or programme, of any sort. A recycled project is what a team under time pressure reaches for.
The brief asks for data integration module. How would you build that?
Decoded from SIH26162 itself: Combines NASA FIRMS thermal anomaly data, land-cover information, and industrial databases. The brief asks for it by name.
The brief asks for ai classification engine. How would you build that?
Decoded from SIH26162 itself: Automatically distinguishes industrial fires from forest fires, agricultural burning, and mining activity. The brief asks for it by name.
The brief asks for gis mapping interface. How would you build that?
Decoded from SIH26162 itself: Visualizes the classified thermal sources and fires as an overlay on standard maps. The brief asks for it by name.
The brief asks for storage and monitoring system. How would you build that?
Decoded from SIH26162 itself: Stores processed data and supports ongoing monitoring of persistent thermal sources. The brief asks for it by name.
Why not use what already exists? Name the closest thing to this that is already running.
A team that has not named the alternative themselves is answering this for the first time in the room.
Which single thing will you demonstrate end to end, start to finish, with nothing skipped?
Ours, not a rule: a narrow thing that fully works survives questioning better than a broad thing that half works. If nobody on the team can name it, that is the finding.
Show me this working: the jury will check if your system can correctly separate industrial fires from natural fires using the required data sources, and whether your GIS interface displays the output clearly as a map overlay.
This is the evaluator read for your problem statement, decoded from the brief's own wording.
Each one is quoted from a gap in the brief, not a guess about your team.
No measurable target
The description does not provide an accuracy percentage or speed target for the AI classification.
No specific user named
The text states the risks to public safety and infrastructure, but never names who will actually operate the software.
What the organisers attached, and what the brief assumes you can get.
Same organisation, same year. Reading two of theirs tells you more about what they care about than reading one.