Published Paper Details:

The research paper introduces an innovative AI-driven web application designed for precise nutritional analysis of fruits and vegetables. The application addresses key challenges in food management, including food identification, freshness evaluation, and nutritional monitoring. By leveraging advanced image recognition technology, users can quickly identify various foods and dishes by taking a photo. This capability provides users with detailed information about ingredients and potential recipes, streamlining meal preparation and promoting informed food choices. The application features a tailored data model for assessing food freshness. By evaluating appearance, smell, and texture, the app can determine the quality of foods, helping users minimize food waste and ensure safer consumption. This is particularly useful for individuals aiming to adopt more sustainable practices in their everyday lives. A standout feature of the application is its nutritional tracker, which provides users with comprehensive nutritional information on different foods. This includes data on calories, macronutrients such as proteins, fats, and carbohydrates, as well as vitamins and minerals. Such detailed information empowers users to monitor their dietary intake more effectively, supporting their health and wellness goals. Incorporating these functionalities into a single web application represents a major advancement in food management and nutrition. Users are equipped with a robust tool to enhance their food-related experiences, making healthier and more sustainable choices. Moreover, the application contributes to global ef orts to reduce food waste and promote healthier eating habits, aligning with the broader objectives of improving public health and environmental sustainability.Overall, this AI-driven web application showcases the potential of integrating modern technology into the realm of nutrition and food management, offering significant benefits to users and society as a whole.