AgriTech AI: Smart Quality Control

Manual quality inspection in agriculture is time-consuming and prone to error. The challenge was to develop an automated system that uses computer vision to track quality trends, detect defects in real-time, and provide actionable analytics for improved decision-making.

We designed an AI-driven dashboard that offers real-time monitoring and defect classification for fruits and vegetables. The system integrates live video feeds for instant analysis, performance statistics for tracking quality over time, and a user-friendly summary screen for efficient inspection management. Its deployed on devices like Raspberry Pi for on-site, real-time analysis.