Haixia Zhang – författare

This book explores integrating behavior prediction with artificial intelligence-driven resource management to provide a transformative framework for optimizing vehicular social networks (VSNs). The book starts by providing an overview of the key issues encountered in VSNs, including the dynamic and unpredictable nature of vehicular mobility, varying communication demands, and the need for efficient resource allocation. A significant portion of the book is dedicated to exploring behavior prediction models for vehicles in VSNs. By analyzing the past movements, interactions, and social behaviors of vehicles, this book presents various prediction algorithms to anticipate future positions, communication patterns, and resource requirements. With behavior prediction as a foundation, the book delves into the design and implementation of intelligent resource management systems for VSNs. It demonstrates how predictive capabilities empower these systems to allocate communication, computing and caching resources dynamically. The book extensively evaluates the proposed intelligent resource management approach through extensive simulations and practical experiments. The results showcase the effectiveness of the system, highlighting significant improvements in network performance compared to traditional resource allocation methods. These findings validate the potential of behavior prediction and intelligent resource management in revolutionizing VSNs. Finally, this book provides conclusions and promising directions, hoping to stimulate future research outcomes in the field of vehicular networks from different perspectives. The book serves as an invaluable resource for researchers, engineers, and industry professionals interested in advancing the field of vehicular networks and harnessing behavior prediction to create efficient, safe, and intelligent VSNs.

Presents a thorough summary of recent advances in microelectronic systems and their applications for personalized healthcare

Integrated Smart Micro-Systems Towards Personalized Healthcare provides up-to-date coverage of developments in smart microelectronics and their applications in health-related areas such as sports safety, remote diagnosis, and closed-loop health management. Using a comprehensive approach to the rapidly growing field, this one-stop resource examines different methods, designs, materials, and applications of systems such as multi-modal sensing biomedical platforms and non-invasive health monitoring sensors.

The book’s five parts detail the core units of micro-systems, self-charging power units, self-driven monitor patches, self-powered sensing platforms, and integrated health monitoring systems. Succinct chapters address topics including multi-functional material optimization, multi-dimensional electrode preparation, multi-scene application display, and the use of multi-modal signal sensing to monitor physical and chemical indicators during exercise. Throughout the text, the authors offer key insights on device performance improvement, reliable fabrication processing, and compatible integration designs.

Integrated Smart Micro-Systems Towards Personalized Healthcare is an essential text for researchers, electronic engineers, entrepreneurs, and industry professionals working in material science, electronics, mechanical engineering, bioengineering, and sensor development.