🦿Technical Implementation Path

Data Collection and Intelligent Analysis

The iPulse Protocol leverages multi-source sensor fusion and deep learning algorithms to continuously collect and analyze user biometrics (such as heart rate, blood oxygen, etc.), utilizing deep neural networks to predict health risks. The protocol employs federated learning technology, ensuring that models analyze data locally and encrypt it, thereby guaranteeing privacy while providing precise feedback.

DePIN Support

iPulse utilizes distributed storage and privacy computing to enable secure data storage and sharing through a global decentralized node network. Health data is transmitted using dynamic encryption technologies, allowing users to securely access, manage, and authorize the use of their data while maintaining privacy. Simultaneously, data is tokenized within the DePIN network, assigning economic value to health data and enabling it for authorized transactions and value circulation.

DeSci Collaboration

iPulse supports decentralized scientific collaboration, allowing health data to be used securely by research institutions while remaining anonymized. The protocol connects researchers with data providers, fostering cross-regional and cross-institutional scientific collaborations that drive innovation in medicine and biotechnology.

iPulse Web3 Technology Implementation Path