A mobile and web platform that uses bus-mounted cameras and edge AI to detect road defects and traffic issues, and displays them on a central GIS dashboard for authorities.
Bharat Electronics Limited · Software
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Decomposed from what the description asks for. Nothing added.
Onboard Video Analysis
Processes camera streams on the bus to detect road defects, traffic density, and pedestrian situations.
Incident Detection Module
Identifies rash driving and hit-and-run events, extracts license plates, and records time and GPS coordinates.
Central GIS Dashboard
Aggregates fleet data to visualize events, congestion heat maps, and road conditions on a map.
Traffic Analytics Tool
Analyzes origin and destination patterns and route delays to support transport authorities.
Both columns are read off the brief's own wording. Nothing here is inferred from the ministry's name.
The evaluators will check if the onboard edge AI can reliably detect road hazards and vehicle numbers while minimizing bandwidth usage. They will also test the central dashboard for accurate GIS mapping, congestion heat maps, and actionable insights.
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.
What hardware specifications or camera resolutions are available on the buses?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
What specific communication protocols should be used to send alerts to the central system?
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 onboard video analysis. How would you build that?
Decoded from SIH26124 itself — Processes camera streams on the bus to detect road defects, traffic density, and pedestrian situations. The brief asks for it by name.
Each one is quoted from a gap in the brief, not a guess about your team.
Needs data you may not get
The solution relies on video feeds from actual bus-mounted cameras traversing city routes, which students cannot easily obtain or simulate realistically.
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.
Pick what you are about to do and copy the prompt. It carries the organisers' own wording, the constraints they never spell out, and an instruction not to invent requirements they never set.
Who has this problem, what already exists, and what you would have to find out.
The brief asks for incident detection module. How would you build that?
Decoded from SIH26124 itself — Identifies rash driving and hit-and-run events, extracts license plates, and records time and GPS coordinates. The brief asks for it by name.
The brief asks for central gis dashboard. How would you build that?
Decoded from SIH26124 itself — Aggregates fleet data to visualize events, congestion heat maps, and road conditions on a map. The brief asks for it by name.
The brief asks for traffic analytics tool. How would you build that?
Decoded from SIH26124 itself — Analyzes origin and destination patterns and route delays to support transport authorities. The brief asks for it by name.
Where does your data come from — a published source, one you collect, or one you generate?
No dataset is attached to this problem statement, so sourcing it is part of the work and nobody told you that.
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 evaluators will check if the onboard edge AI can reliably detect road hazards and vehicle numbers while minimizing bandwidth usage.
This is the evaluator read for your problem statement, decoded from the brief's own wording.
Show me this working: they will also test the central dashboard for accurate GIS mapping, congestion heat maps, and actionable insights.
This is the evaluator read for your problem statement, decoded from the brief's own wording.