PS-05Agriculture & Food Systems
KisanMitra
AI Decision Support for Small-Farmer Crop Risk and Action
SDG 2SDG 15
The challenge
Small farmers often receive separate advice about crop disease, weather, irrigation and market conditions, making it difficult to decide what action matters most at a particular time. Build an AI-assisted farmer support system for one clearly defined crop and region. It should combine a small set of practical inputs such as crop image, growth stage, recent weather, soil or irrigation status and local market information to identify a likely risk and recommend a limited set of evidence-based next actions. The system should state uncertainty and must not present unvalidated pesticide or medical-style claims as guaranteed advice.
What a working submission needs
Create a working prototype for one crop that supports image or structured symptom input, risk classification, weather-aware advice and a simple market or resource view.
Demonstrate the complete farmer journey with sample data and report model/logic limitations.
Stretch goals
offline regional-language support, explainable image regions, irrigation scheduling or farmer-group aggregation.
Optional. A working core counts for more than feature count.Suggested stack
Web/mobile application, AI/ML models, a mapping or dashboard interface, and open APIs as appropriate to the problem.
Scope and responsibility
Healthcare, safety and public-sector challenges are decision-support tools, not autonomous clinical, legal, emergency-command or enforcement systems. Name your prototype’s limitations in the demo. Judging weighs a working core, justified use of AI, technical quality, real-world impact and responsible design above feature count.
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