Byte Bite-AI

Byte Bite-AI is an AI-driven healthy eating assistant designed to provide personalised dietary recommendations to university students, with a special focus on social dining experiences. Built on Python Flask, Byte Bite-AI leverages Rule-Based AI to offer dietary suggestions for a variety of dining options available at Campus Hubs.

BB-AI Project Demo Video - Click Below Thumbnail

BB-AI Marketing Promo Video - Click Below Logo

BB-AI Deep Dive Podcast (generated by NotebookLM) - Click Below Thumbnail

Key Features

• Personalized Recommendations: Byte Bite-AI analyzes individual dietary preferences and makes recommendations tailored to user needs.
• AI-Powered Decision-Making: The system integrates Explainable AI (XAI) to enhance transparency in dietary suggestions.
• Multi-Platform Support: Works seamlessly across desktop and mobile web interfaces.
• Chatbot Assistance: AI-driven chatbot to provide real-time meal suggestions and answer nutrition-related queries, powered by Orca:Mini running locally on Ollama, ensuring enhanced privacy and responsiveness.
• Augmented Reality (AR) Integration: Uses Google Teachable Machine to recognize restaurant logos and display nutritional insights.
• Dining Insights: Real-time suggestions from 8 dining options at Campus Hub, facilitating healthy eating in social settings.
• Profile & Goal Tracking: Allows users to track their weight and progress towards dietary goals.
• Scalable Design: Built with a modular architecture that allows for future expansions.

Technical Details

• Frontend: HTML, CSS, JavaScript with localStorage for data management.
• Backend: Python Flask for serving dynamic content and handling user data.
• Data Storage: User credentials and preferences are stored securely in JSON files and localStorage for seamless user experience.
• AI & Machine Learning:
  • Utilizes Rule-Based AI for meal recommendations.
  • Employs Orca-Mini (via Ollama) for chatbot responses.
  • Uses Google Teachable Machine for AR-powered food recognition.
• Security & Privacy:
  • Implements password hashing and secure session tracking.
  • Ensures AI-generated responses do not access or store personal data.

Motivation

The main motivation behind Byte Bite-AI is to encourage healthy eating habits among University of Malta students. Recognizing the difficulties students face in balancing a healthy lifestyle with academic and social obligations, Byte Bite-AI offers a smart solution to make healthier choices more accessible and simple.

By integrating intelligent dietary recommendations, Byte Bite-AI hopes to create an engaging and intuitive interface. This assistant enables students to make informed, health-conscious dining decisions with friends by providing personalized guidance in real time, thereby supporting both individual wellness goals and a healthier campus culture.

Outlets which Byte Bite-AI Works On

Clone the repository:

  git clone https://github.com/AFLucas-UOM/Byte-Bite-AI.git

To Start the Server for Local Devices

flask --app flask-app run --host=0.0.0.0 --port=2000

Future Work

Byte Bite-AI aims to expand its functionality with the following features:

• Native iOS & Android App: Development of a standalone mobile application.
• Federated Learning Implementation: Enhancing recommendation accuracy without compromising user privacy.
• Expanded AR Features: Integrating AI-powered real-time food classification and calorie tracking.
• Chatbot Enhancements: Improving response accuracy and personalization for meal suggestions.
• Partnerships with Restaurants: Direct collaboration for menu updates and healthy food promotions.

Acknowledgments

This project was developed as part of the ICS3211 course at the University of Malta.

Contact

For inquiries or feedback, please contact Andrea Filiberto Lucas & Sean David Muscat