Wearable AI Architecture for Continuous Health Monitoring
Abstract
Wearable artificial intelligence (AI) has emerged as a transformative technology for continuous health monitoring, enabling real-time physiological sensing, intelligent data interpretation, and proactive healthcare delivery. This chapter presents a comprehensive overview of wearable AI architecture, focusing on the integration of biosensors, edge intelligence, communication frameworks, and cloud-assisted analytics for uninterrupted health surveillance. The architecture emphasizes low-power operation, real-time decision-making, and adaptive learning to support long-term monitoring of vital signs such as heart rate, activity patterns, sleep quality, and metabolic indicators. Key design considerations, including data security, privacy preservation, interoperability, and scalability, are discussed in the context of personalized and preventive healthcare. The chapter further explores the role of edge AI and federated learning in reducing latency and preserving user data confidentiality. By highlighting current applications, challenges, and future directions, this chapter provides valuable insights for researchers, engineers, and healthcare professionals aiming to develop intelligent, reliable, and user-centric wearable health monitoring systems.