Mobile diet and calories tracker

Low, Wei Jia (2026) Mobile diet and calories tracker. Final Year Project, UTAR.

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Abstract

This project presents the development of a comprehensive Malaysian Diet Management Mobile Application that aims to improve the accuracy, personalization, and accessibility of dietary tracking for users with various health and fitness goals. The system integrates advanced image recognition technology using the CLIP model to enable users to log meals by simply taking a photo, significantly reducing manual input while providing more accurate calorie and nutrient estimation. A key feature of the application is its ability to deliver condition-specific dietary recommendations for users with medical conditions such as diabetes, hypertension, and high cholesterol. The system also includes personalized meal planning, daily calorie distribution, and intelligent food suggestions based on the user’s health profile, dietary preferences, and Malaysian local cuisine. Educational resources on nutrition and healthy eating habits are incorporated to promote long-term behavioral change. The mobile application is developed using Flutter, with Firebase serving as the backend for authentication and real-time data management. A Flask backend powered by the CLIP model handles food image recognition, while nutritional information is retrieved from the USDA FoodData Central database. The combination of these technologies creates a seamless, user-friendly, and intelligent diet management solution tailored for Malaysian users. The project successfully demonstrates how modern technologies such as machine learning and cloud services can be effectively integrated to support healthier dietary habits in a practical and accessible manner.

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