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5G IoT and Edge Computing for Smart Healthcare: Intelligent Data-Centric Systems

Editat de Akash Kumar Bhoi, Victor Hugo Costa de Albuquerque, Samarendra Nath Sur, Paolo Barsocchi
en Limba Engleză Paperback – 29 mar 2022
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.


  • Focuses on the advancement of 5G in terms of its security and privacy aspects, which is very important in health care systems
  • Address advancements in signal processing and, more specifically, the cognitive computing algorithm to make the system more real-time
  • Gives insights into various information-processing models and the architecture of layers to realize a 5G based smart health care system
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Specificații

ISBN-13: 9780323905480
ISBN-10: 032390548X
Pagini: 324
Ilustrații: 90 illustrations (60 in full color)
Dimensiuni: 191 x 235 x 23 mm
Greutate: 0.56 kg
Editura: ELSEVIER SCIENCE
Seria Intelligent Data-Centric Systems


Cuprins

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