Intelligent IoT Systems in Personalized Health Care

delivers a significant forum for the technical advancement of IoMT learning in parallel computing environments across biomedical engineering diversified domains and its applications. Pursuing an interdisciplinary approach, the book focuses on methods used to identify and acquire valid, potentially useful knowledge sources. The book presents novel, in-depth, fundamental research contributions from a methodological/application perspective to help readers understand the fusion of AI with IoT and its capabilities in solving a diverse range of problems for biomedical engineering and its real-world personalized health care applications.

The book is well suited for researchers exploring the significance of IoT based architecture to perform predictive analytics of user activities in sustainable health.

Key Highlights

Presents novel, in-depth, fundamental research contributions from a methodological/application perspective to help readers understand the fusion of AI with IoT

Illustrates state-of-the-art developments in new theories and applications of IoMT techniques as applied to parallel computing environments in biomedical engineering systems

Presents concepts and technologies successfully used in the implementation of today’s intelligent data-centric IoT systems and Edge-Cloud-Big data