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@article{175062,
        author = {CHRISTO KURIAN TOMY and Jyothish S and Alan Eldho Saji and Bhavna Boby},
        title = {Food Spoilage Detection & Expiration Tracking System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {1608-1612},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175062},
        abstract = {Food spoilage and contamination pose serious risks to households and the food industry, leading to health hazards, financial losses, and increased waste. This project introduces a food spoilage and expiration tracking system that detects spoilage early and provides real-time alerts. Using IoT, machine learning, and computer vision, the system monitors food quality based on gas emissions, temperature, humidity, and visual indicators. It integrates MQ-135 and DHT11 sensors with an ESP-32 camera module to collect data, which is analysed using a YOLOv8 model for visual inspection. A user-friendly mobile and web application allows users to track freshness, receive alerts, and access recipe suggestions to minimise waste. Designed for seamless integration with smart home devices, this cost-effective and scalable solution enhances food safety. By leveraging advanced technology, the system aims to reduce food loss, improve consumer awareness, and promote sustainable food management.},
        keywords = {IoT, machine learning, Computer Vision, Food Spoilage.},
        month = {April},
        }