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@article{181493,
        author = {Mohammed Liyaqat Al Zama and Mustafa Syed and Syed Anwar Ali and Syed Mohammed Mehdi Abidi},
        title = {A Personalized AI-Based Nutrition Tracking App},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {3944-3949},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=181493},
        abstract = {The increasing demand for personalized health solutions has led to a surge in nutrition-based mobile applications. However, many existing tools fail to offer AI-driven meal planning, offline usability, or culturally relevant food databases. This project introduces Nutrimate, an AI-powered nutrition tracking app developed using React Native, Express, and MongoDB. Nutrimate helps users set fitness goals such as weight loss, maintenance, or muscle gain, and offers real-time calorie insights through barcode scanning and local food recognition. The app also includes offline support and progress tracking for enhanced accessibility. Data is stored locally using AsyncStorage, and navigation is implemented through Stack, Tab, and Drawer navigators. Compared to other apps that rely solely on static food entries or cloud dependency, Nutrimate provides a lightweight, goal-oriented approach tailored for Indian users. The system architecture and design ensure modular scalability and strong user engagement. Evaluation results show increased user satisfaction and improved tracking accuracy, indicating promise for further integration with wearable devices and public health tools},
        keywords = {AI Nutrition App, Personalized Diet Tracking, React Native, HealthTech, Offline Food Logging},
        month = {June},
        }