Advancing Wearable Health and Sports Monitoring Through an Edge-Cloud AI Continuum. Invited Paper

Abstract

The H2TRAIN project proposes a comprehensive edge-cloud AI continuum for real-time, secure, and personalized health and performance monitoring through wearable technologies. By integrating in vivo physiological measurements, artificial intelligence, and biometric encryption, H2TRAIN addresses the growing demand for adaptive digital health solutions. The system leverages embedded intelligence at the edge to perform immediate data processing and personalized analytics, while offloading complex tasks to fog and cloud layers for scalability. In vivo measurements enable the development of AI models that reflect real-world conditions, ensuring accuracy and ecological validity. At the same time, biometric cryptographic techniques based on physiological signals guarantee data security and user authentication, even in dynamic and uncontrolled environments. H2TRAIN establishes a secure, intelligent, and energy-efficient infrastructure applicable to clinical, rehabilitation, and sports domains.