A dashboard for SAIL logistics managers that predicts overseas bulk freight rates and recommends optimal vessel types, charter timing, and routes to reduce logistics costs.
Ministry of Steel · SAIL · Software
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Decomposed from what the description asks for. Nothing added.
Freight Forecasting Engine
Uses time series and regression models to predict future freight rates across specific shipping routes and vessel classes.
Port Infrastructure Matcher
Filters eligible vessel sizes by checking cargo volume against physical port constraints like draft, length overall, and handling speeds.
Charter Timing Optimizer
Analyzes market trends to recommend the best time window for signing short-term or medium-term charter contracts.
Risk and Congestion Monitor
Tracks port congestion and market volatility to issue early warning alerts to supply chain managers.
Logistics Decision Portal
A web dashboard where users enter cargo details and port pairs to generate cost predictions and routing recommendations.
Both columns are read off the brief's own wording. Nothing here is inferred from the ministry's name.
Evaluators will check if the model accounts for explicit port constraints like draft, beam, length overall, and handling rates at specified East Coast Indian ports. They will assess whether the solution provides actionable entry timing recommendations instead of just raw price charts. They will also look for integration of multiple inputs like commodity trends and vessel types.
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 source or API access for real-time freight rates and port congestion data?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Target prediction accuracy percentage or error threshold?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Minimum historical time period required for model training?
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.
No dataset provided
The description depends on real data, and the organisers have not attached a dataset link.
Needs data you may not get
The problem requires historical global freight rates and real-time port congestion data, which are typically locked behind expensive commercial subscriptions.
No measurable target
The text asks for a high degree of accuracy without defining any quantitative metric or percentage target.
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 freight forecasting engine. How would you build that?
Decoded from SIH26006 itself — Uses time series and regression models to predict future freight rates across specific shipping routes and vessel classes. The brief asks for it by name.
The brief asks for port infrastructure matcher. How would you build that?
Decoded from SIH26006 itself — Filters eligible vessel sizes by checking cargo volume against physical port constraints like draft, length overall, and handling speeds. The brief asks for it by name.
The brief asks for charter timing optimizer. How would you build that?
Decoded from SIH26006 itself — Analyzes market trends to recommend the best time window for signing short-term or medium-term charter contracts. The brief asks for it by name.
The brief asks for risk and congestion monitor. How would you build that?
Decoded from SIH26006 itself — Tracks port congestion and market volatility to issue early warning alerts to supply chain managers. The brief asks for it by name.
The brief asks for logistics decision portal. How would you build that?
Decoded from SIH26006 itself — A web dashboard where users enter cargo details and port pairs to generate cost predictions and routing recommendations. 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: evaluators will check if the model accounts for explicit port constraints like draft, beam, length overall, and handling rates at specified East Coast Indian ports.
This is the evaluator read for your problem statement, decoded from the brief's own wording.
Show me this working: they will assess whether the solution provides actionable entry timing recommendations instead of just raw price charts.
This is the evaluator read for your problem statement, decoded from the brief's own wording.