FLORA: Federated Learning Ovulation Tracking App with Reward System

FLORA is an innovative ovulation tracking app that harnesses Federated Learning to promote transparency and enhance users’ privacy. This cutting-edge approach ensures that data remains on users’ devices while enabling the collaborative training of machine learning models.

FLORA offers accurate ovulation date predictions and personalized health insights using Artificial Intelligence. To bolster security, additional privacy-preserving mechanisms are employed. Fully Homomorphic Encryption is applied during the model aggregation phase to shield user data from potential breaches, while local differential privacy is integrated to ensure data privacy from model-based threats. Furthermore, FLORA leverages blockchain technology to establish a verifiable consent system. This system verifies each user’s consent for data sharing and prevents unauthorized alterations. Blockchain also serves as a transparent repository for storing machine learning model versions generated during the Federated Learning process. Lastly, to recognize and incentivize user participation, FLORA introduces a token-based blockchain reward system for users who contribute models or data commensurate with their contributions.

The project’s ultimate objective is the development of a user-oriented mobile application for precise ovulation tracking with total control over data, enhanced by the power of AI. This solution places the utmost importance on safeguarding user privacy and machine learning transparency through state-of-the-art techniques, ensuring that individuals can confidently use FLORA for their health and well-being needs.