An AI-Driven Framework for Personalized Diet Generation and Nutrition Suggestions Using Machine Learning, Computer Vision and NLP

To counteract unhealthy eating habits among the younger generation, a novel and economical AI-powered framework has been developed to serve as a virtual nutritionist and nutrition counsellor. The system uses machine learning, computer vision, and natural language processing to provide personalized nutrition plans via an easy-to-use online application. It generates tailored meal plans that consider user preferences, allergies, and meal times by calculating Body Mass Index (BMI) based on user input. In addition to blog links and tailored training regimens (enhanced by the LLM3 model trained on a Kaggle gym dataset), a feedback mechanism allows for continuous optimization. Real-time food classification uses VGG16 and ResNet deep learning models to detect damaged or harmful foods and send out alerts for unsuitable foods. Additionally, integration with Google Maps and KNN helps users locate nearby dietitians, fostering better access to professional guidance. These comprehensive improvements significantly contribute to maintaining a good diet.