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PS 26031SOFTWAREFitness & SportsFast Prototype (36h)

Quality assessment and grading of onions are often subjective and vary across procurement centers, resulting in disputes and inconsistencies.

Ministry of Consumer Affairs, Food & Public Distribution• Department of Consumer Affairs (DoCA)
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30-Second Plain English Summary

Manual quality assessment of onions in agricultural mandis is subjective and prone to dispute, leading to unfair pricing for farmers and high storage losses from rotten bulbs. Build an AI computer vision grading and sorting platform combining multi-spectral/optical imaging to grade onions by diameter size, detect skin defects (sprouting, black mold, neck rot), and calculate batch market value.

5-Dimension Strategic ScorecardOverall Score: 3.7 / 5.0
Innovation
3.7 / 5
36h Feasibility
4.5 / 5
Uniqueness
3.5 / 5
Jury Appeal
3.5 / 5
Tech Depth
3.5 / 5
Recommended System Architecture Pipeline
Conveyor / Box Camera Setup -> Edge Inference Module (YOLOv8 ONNX) -> FastAPI Quality Engine -> e-NAM Auction Bus -> Farmer Mandi PWA
Recommended Tech StackClick to search similar
Official Government Problem Description
Expected Solution: Develop an AI-based mobile application that: • Uses image processing to assess onion quality. • Identifies damaged, rotten, sprouted, or undersized onions. • Estimates Grade A and URS percentages. • Generates a digital quality report instantly. • Reduces human bias and improves transparency.
AI & PPT Citation Format

Smart India Hackathon 2026 Problem Statement PS-26031: "Quality assessment and grading of onions are often subjective and vary across procurement centers, resulting in disputes and inconsistencies.", Ministry: Ministry of Consumer Affairs, Food & Public Distribution. Strategy & Architecture via SIH ONE (https://sihone.pages.dev/ps/26031)

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