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@article{175785,
        author = {Boosireddygari Uday Kiran Reddy and T. RajyaLakshmi},
        title = {Scalable and Efficient Food Quality Monitoring Using CNN for Supply Chain Optimization},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {5018-5021},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175785},
        abstract = {Ensuring the accurate prediction of the Remaining Shelf-Life (RSL) for Fresh Fruits and Vegetables (FFVs) during transportation is vital for effective planning and cost management. The Internet of Things (IoT) allows real-time processing of environmental data, but existing RSL models are often qualitative, invasive, or static. This study presents a new, validated RSL model that dynamically estimates general decay rates based on respiration rates, integrating them over time. Unlike previous methods, it is non-invasive and does not require pre-deployment experiments. A simplified surrogate model was also developed to facilitate real-time applications in IoT systems. Testing with various fresh products showed minimal prediction errors, proving the model's reliability.},
        keywords = {Remaining Shelf Life (RSL), Fresh Fruits and Vegetables (FFVs), Internet of Things (IoT), Transportation},
        month = {April},
        }