A mobile-based conversational AI chatbot that lets users ask for weather forecasts, warnings, and climate data in multiple Indian languages and via voice.
Ministry of Earth Sciences (MoES) · India Meteorological Department · Software
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Decomposed from what the description asks for. Nothing added.
Conversational UI
A mobile interface supporting natural language text and voice interactions for users.
LLM Query Engine
An AI engine that understands weather queries and retrieves information from connected databases.
Data Ingestion Backend
A scalable backend that connects with weather APIs, databases, and forecast models.
Multilingual Module
Translation and processing support for multiple Indian languages.
Alert System
A feature to disseminate extreme weather alerts and location-based advisories.
Both columns are read off the brief's own wording. Nothing here is inferred from the ministry's name.
The evaluators will test accuracy, response latency, multilingual capability, voice-enabled interaction, scalability, and integration with real-time meteorological systems.
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.
Which specific numerical weather prediction models or APIs will be accessible to students?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
The exact list of Indian languages that must be supported?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
What latency threshold counts as success?
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 conversational ui. How would you build that?
Decoded from SIH26068 itself: A mobile interface supporting natural language text and voice interactions for users. The brief asks for it by name.
The brief asks for llm query engine. How would you build that?
Decoded from SIH26068 itself: An AI engine that understands weather queries and retrieves information from connected databases. The brief asks for it by name.
The brief asks for data ingestion backend. How would you build that?
Decoded from SIH26068 itself: A scalable backend that connects with weather APIs, databases, and forecast models. The brief asks for it by name.
The brief asks for multilingual module. How would you build that?
Decoded from SIH26068 itself: Translation and processing support for multiple Indian languages. The brief asks for it by name.
The brief asks for alert system. How would you build that?
Decoded from SIH26068 itself: A feature to disseminate extreme weather alerts and location-based advisories. 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 test accuracy, response latency, multilingual capability, voice-enabled interaction, scalability, and integration with real-time meteorological systems.
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 lists evaluation parameters like response latency and accuracy without specifying any measurable numerical targets for them.
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.