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@article{194167,
        author = {Bandili Ashok},
        title = {AI-Based Personalized Nutrition Vending Machine: An IoT and Machine Learning Approach to Combat Lifestyle Diseases},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {2903-2910},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=194167},
        abstract = {Modern lifestyle patterns have contributed to a global surge in obesity, diabetes, and related lifestyle diseases. Traditional vending machines in public spaces predominantly offer high-calorie, nutrient-poor snacks without considering individual nutritional needs. This paper presents an AI-based personalized nutrition vending machine that integrates IoT sensors, embedded computing, and machine learning to provide real-time dietary recommendations. The system measures user height and weight using Time-of-Flight (ToF) sensors and load cells, calculates Body Mass Index (BMI), and classifies users into health categories (underweight, normal, overweight, obese). Based on this classification, the machine recommends appropriate food items and dispenses selected products. This intelligent system promotes healthier eating habits in public environments such as gyms, schools, hospitals, and corporate offices. The proposed solution addresses critical gaps in automated retail by combining health monitoring with personalized nutrition guidance, offering a scalable platform to combat rising lifestyle disease prevalence in India and globally.},
        keywords = {IoT, Artificial Intelligence, Personalized Nutrition, Vending Machine, BMI Classification, Health Monitoring, Embedded Systems.},
        month = {March},
        }