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@article{204773,
        author = {Nilesh Kumar and Noor Hasan and Prem Kumari verma},
        title = {Food Junction 2.0: AI-Powered Predictive Meal Delivery System with Dynamic Nutritional Optimization for Railway Passengers},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {5412-5417},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=204773},
        abstract = {This paper introduces Food Junction 2.0a high-tech AI-based predictive meal delivery system dedicated to railway passengers, with a dynamic nutrition optimization and hyper personalization. In comparison with traditional food delivery systems, ours uses deep learning with algorithms to forecast passenger preferences of meals, depending on their journeys, their health profiles and other situational factors such as travelling time, the type of classes, and the local factors. The system combines real-time biometric information (where the user grants permission), using APIs of wearable devices, to adapt meal suggestions in real time to accommodate everyday health problems associated with traveling, including indigestion, dehydration, and fatigue. The system predicts with accuracy 94.3% with the help of a hybrid architecture integrating Graph Neural Networks to model the preferences and Reinforcement Learning to optimize the delivery, saving 68% of food waste in comparison to the classical systems. In 500-participant clinical trials, the efficacies of the intervention are shown in terms of the passenger well-being index, such as 41% decrease in travel fatigue and 33% enhancement of the digestive comfort on the trip. This study introduces a paradigm shift which is the reactive food ordering to the proactive nutritional management in transit environments.},
        keywords = {AI-Powered Food Delivery, Predictive Analytics, Nutritional Optimization, Railway Services, Personalization, Health Informatics},
        month = {June},
        }