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5G IoT and Edge Computing for Smart Healthcare
Covers the latest trends in data processing related 5G IoT and edge computing for successful implementation of a smart health care system
Akash Kumar Bhoi (Edited by), Victor Hugo Costa de Albuquerque (Edited by), Samarendra Nath Sur (Edited by), Paolo Barsocchi (Edited by)
9780323905480, Elsevier Science
Paperback / softback, published 29 March 2022
324 pages, 90 illustrations (60 in full color)
23.5 x 19 x 2.1 cm, 0.68 kg
5G IoT and Edge Computing for Smart Healthcare addresses the importance of a 5G IoT and Edge-Cognitive-Computing-based system for the successful implementation and realization of a smart-healthcare system. The book provides insights on 5G technologies, along with intelligent processing algorithms/processors that have been adopted for processing the medical data that would assist in addressing the challenges in computer-aided diagnosis and clinical risk analysis on a real-time basis. Each chapter is self-sufficient, solving real-time problems through novel approaches that help the audience acquire the right knowledge. With the progressive development of medical and communication - computer technologies, the healthcare system has seen a tremendous opportunity to support the demand of today's new requirements.
1. Fundamentals and architecture of edge computing platform: 5G IoT/IoMT
2. Physical layer architecture of 5G enabled IoT/IoMT system
3. HetNet/M2M/D2D communication in 5G technologies
4. Sensor Networks: Data and Traffic Models in 5G Network
5. Convergent Network Architecture of 5G and MEC
6. Privacy and Security aspect of MEC enabled 5G- IoT network
7. Healthcare data encryption, data processing for the data acquired from smart sensors and smart city healthcare approaches
8. Artificial Neural Networks/ Deep Learning approaches for the disease diagnosis and treatment
9. Advanced pattern recognition tools/ computer vision algorithm for the disease diagnosis
10. Cognitive computing for the data cognition for the information relevant to the user’s disease and resource management
11. Computational Intelligence in Human-machine interface (HMI) for telemedicine application
12. Case Study: challenges and implications of smart healthcare applications and solutions to address these challenges
Subject Areas: Expert systems / knowledge-based systems [UYQE], Artificial intelligence [UYQ], Robotics [TJFM1], Electronic devices & materials [TJFD], Electronics & communications engineering [TJ]
