A software system that uses satellite images and vessel tracking data to detect sea oil spills, trace their origin, and identify the responsible ship.
National Technical Research Organisation (NTRO) · Software
Signing in saves it for your whole team, so everyone on your invite link sees the same two entries. Anything you shortlisted while signed out comes with you.
Decomposed from what the description asks for. Nothing added.
Spill Detection Pipeline
An automated pipeline that processes SAR and EO satellite imagery to detect and characterise oil spills.
Drift Prediction Module
A module using oceanographic and meteorological data to trace the oil slick back to its origin and predict future flow.
Vessel Correlation Engine
A scoring system that analyses historic AIS data to filter traffic and rank suspect vessels near the origin window.
Visual Interface
A software dashboard that displays detected slicks, drift paths, and ranked suspect vessels.
Both columns are read off the brief's own wording. Nothing here is inferred from the ministry's name.
The jury will check if the automated pipeline can successfully detect oil slicks from satellite imagery, accurately trace the drift paths, and correctly rank suspect vessels using AIS data correlation.
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 satellite datasets or formats to be used?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Target accuracy metrics for oil spill detection or vessel identification?
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 spill detection pipeline. How would you build that?
Decoded from SIH26143 itself: An automated pipeline that processes SAR and EO satellite imagery to detect and characterise oil spills. The brief asks for it by name.
The brief asks for drift prediction module. How would you build that?
Decoded from SIH26143 itself: A module using oceanographic and meteorological data to trace the oil slick back to its origin and predict future flow. The brief asks for it by name.
The brief asks for vessel correlation engine. How would you build that?
Decoded from SIH26143 itself: A scoring system that analyses historic AIS data to filter traffic and rank suspect vessels near the origin window. The brief asks for it by name.
The brief asks for visual interface. How would you build that?
Decoded from SIH26143 itself: A software dashboard that displays detected slicks, drift paths, and ranked suspect vessels. 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 the automated pipeline can successfully detect oil slicks from satellite imagery, accurately trace the drift paths, and correctly rank suspect vessels using AIS data correlation.
This is the evaluator read for your problem statement, decoded from the brief's own wording.
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.