Smart Fridge with Personalized Recipe Recommendation system

This work intends to create a smart recipe recommendation system that makes use of deep learning and computer vision technologies to recognize and categorize veggies in a user’s refrigerator to address these issues. The system will employ an ESP32 camera module to take live photographs of the vegetables to precisely identify and classify each vegetable. These images will then be loaded into a deep learning YOLOv9 model which is integrated with app. The app will offer recipe suggestions based on the user’s tastes and nutritional needs when the algorithm has identified the vegetables in the refrigerator. The users can tailor their nutritional needs, such as veganism, gluten-free eating, or other preferences through the app. The software will suggest meals that fit the user’s preferences based on the available vegetables, reducing food waste, and enhancing healthy meal preparation. The app will allow users to generate shopping lists based on the products they already have and the dishes they intend to make, in addition to offering personalized recipe ideas.