Secure Lateral Flow Test Reader Development

The project aims to develop essential components of an open-source health platform for Rapidte.st by Abundant.Science. The platform's primary function is to accurately read lateral flow tests, securely store the results, and facilitate sovereign data sharing. The project will implement Signal Protocol for end-to-end encryption, ensuring that all data transactions are secure and private. Additionally, AI-powered algorithms will be integrated to enhance the accuracy and reliability of test readings. The project is designed to be completed within 60 hours over four weeks, allowing learners to apply their knowledge of encryption, AI, and software development. The goal is to create a robust, user-friendly system that can be easily integrated into existing health platforms, providing a secure and efficient solution for managing lateral flow test data. Project creation considerations: Students should have strong software development skills Experience with mobile development, encryption protocols, and AI/ML preferred Work can be completed remotely with regular team collaboration Tasks are modular but interconnected, requiring good communication Project Scope and Expectations: Students will develop a mobile-first application capable of capturing, analyzing, and securely storing rapid test results. The platform will implement the Signal Protocol for end-to-end encryption while maintaining HIPAA/PHIPA compliance and enable sovereign control over health data sharing. Benefits for Students: Hands-on experience with cutting-edge security protocols Real-world AI/ML implementation Exposure to healthcare compliance requirements Portfolio piece demonstrating full-stack development Open-source contribution experience