Automating Quality Control with Real-Time Imaging
Our project leverages cutting-edge smart vision technology and AI-driven algorithms to revolutionize quality control and freshness detection in the Quick Commerce industry. By integrating OCR for automated data extraction, real-time imaging, and advanced analytics, we streamline operations such as billing, inventory management, and product classification. Key features include automated product counting, brand matching, and flavor detection, along with a powerful freshness prediction system for produce. Utilizing open-source datasets and machine learning models, the system enhances supply chain efficiency, reduces waste, and ensures customer satisfaction with accurate, real-time insights.
During the Project, we combined expertise in full-stack development and AI to deliver impactful results. Key features implemented included OCR-based product detection for automating data extraction, AI-powered freshness prediction for produce shelf life, and real-time analytics for inventory management. Through rapid prototyping, we integrated advanced imaging algorithms for defect detection and classification. Real-time testing and debugging ensured high accuracy and reliability. Our teamwork and innovation addressed quality control and quick commerce challenges.