AgriTech AI: Smart Quality Control
Computer Vision for Agriculture
AI-Powered Agriculture Quality Control System with real-time defect detection, live monitoring, and actionable analytics.
Role
Product Designer
Year
2023
Tools
Figma, Python, YOLO
Category
AgriTech
Project Gallery
3 screens — click to expandThe Challenge
Manual quality inspection in agriculture is slow, inconsistent, and labor-intensive. Defects missed at inspection reached consumers — damaging brand trust and creating financial waste.
My Role
Designed the full AI dashboard product experience — from live camera feed UI, defect classification display, analytics views, to the summary reporting screen for daily quality oversight.
What I Found
Field visits to 2 packing facilities revealed inspectors were managing multiple conveyor lines simultaneously
Cognitive overload was the root problem — they couldn't watch everything
The system needed to notify, not demand constant attention
The Solution
Designed an AI-driven dashboard with real-time defect flagging, sound alerts for high-severity items, and clean analytics charts for trend tracking. Deployed on Raspberry Pi for on-site edge processing.
Real-time Defect Detection
Reduced Manual Effort
Detailed Analytics
Optimised Quality Control
