An autonomous drone with on-board AI that uses RGB and thermal cameras to locate survivors and detect hazards in disaster zones without relying on internet connectivity.
Qualcomm Inc · Hardware
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Decomposed from what the description asks for. Nothing added.
Autonomous Navigation
The drone must navigate using GPS, SLAM, and obstacle avoidance in damaged environments.
On-Device AI Inference
The system must process camera feeds locally to detect people and hazards without cloud connection.
Multi-Sensor Fusion
Integrate RGB cameras, thermal cameras, IMU, and GPS sensors to locate victims accurately.
Geo-Tagged Mapping
Generate live maps showing survivor locations, hazard zones, and safe access routes.
Command Center Dashboard
Build a dashboard to display drone feeds, detected survivors, and mission status for agencies.
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 drone can navigate without GPS, run AI inference locally on device without cloud connectivity, and handle multiple sensors like RGB and thermal cameras.
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 specific hardware platform or drone frame must be used?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
What exact accuracy is required for survivor and hazard detection?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
What payload weight limits apply to the drone?
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.
Each one is quoted from a gap in the brief, not a guess about your team.
Needs physical hardware
Listed as a hardware problem statement, so a working demo needs physical components you have to source yourself.
Needs data you may not get
Building and testing an autonomous disaster-response drone requires specialized hardware and physical testing environments that students typically cannot access.
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 autonomous navigation. How would you build that?
Decoded from SIH26177 itself — The drone must navigate using GPS, SLAM, and obstacle avoidance in damaged environments. The brief asks for it by name.
The brief asks for on-device ai inference. How would you build that?
Decoded from SIH26177 itself — The system must process camera feeds locally to detect people and hazards without cloud connection. The brief asks for it by name.
The brief asks for multi-sensor fusion. How would you build that?
Decoded from SIH26177 itself — Integrate RGB cameras, thermal cameras, IMU, and GPS sensors to locate victims accurately. The brief asks for it by name.
The brief asks for geo-tagged mapping. How would you build that?
Decoded from SIH26177 itself — Generate live maps showing survivor locations, hazard zones, and safe access routes. The brief asks for it by name.
The brief asks for command center dashboard. How would you build that?
Decoded from SIH26177 itself — Build a dashboard to display drone feeds, detected survivors, and mission status for agencies. 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 drone can navigate without GPS, run AI inference locally on device without cloud connectivity, and handle multiple sensors like RGB and thermal cameras.
This is the evaluator read for your problem statement, decoded from the brief's own wording.