5G IoT and Edge Computing for Smart Healthcare

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 INDICE: 1. Fundamentals and architecture of edge computing platform: 5G IoT/IoMT2. Physical layer architecture of 5G enabled IoT/IoMT system3. HetNet/M2M/D2D communication in 5G technologies4. Sensor Networks: Data and Traffic Models in 5G Network5. Convergent Network Architecture of 5G and MEC6. Privacy and Security aspect of MEC enabled 5G- IoT network7. Healthcare data encryption, data processing for the data acquired from smart sensors and smart city healthcare approaches8. Artificial Neural Networks/ Deep Learning approaches for the disease diagnosis and treatment9. Advanced pattern recognition tools/ computer vision algorithm for the disease diagnosis10. Cognitive computing for the data cognition for the information relevant to the user's disease and resource management11. Computational Intelligence in Human-machine interface (HMI) for telemedicine application12. Case Study: challenges and implications of smart healthcare applications and solutions to address these challenges

• ISBN: 978-0-323-90548-0
• Editorial: Academic Press
• Encuadernacion: Rústica
• Páginas: 324
• Fecha Publicación: 29/03/2022
• Nº Volúmenes: 1
• Idioma: Inglés