| Description |
1 online resource |
|
text rdacontent |
|
computer rdamedia |
|
online resource rdacarrier |
| Series |
Intelligent data centric systems
|
| Contents |
Edge-IoMT-based enabled architecture for smart healthcare system -- Physical layer architecture of 5G enabled IoT/IoMT system -- HetNet/M2M/D2D communication in 5G technologies -- An overview of low power hardware architecture for edge computing devices -- Convergent network architecture of 5G and MEC -- An efficient lightweight speck technique for edge-IoT-based smart healthcare systems -- Deep learning approaches for the cardiovascular disease diagnosis using smartphone -- Advanced pattern recognition tools for disease diagnosis -- Brain-computer interface in Internet of Things environment -- Early detection of COVID-19 pneumonia based on ground-glass opacity (GGO) features of computerized tomography (CT) angiography -- Applications of wearable technologies in healthcare: an analytical study. |
|
Front Cover -- 5G IoT and Edge Computing for Smart Healthcare -- Copyright Page -- Contents -- List of contributors -- 1 Edge-IoMT-based enabled architecture for smart healthcare system -- 1.1 Introduction -- 1.2 Applications of an IoMT-based system in the healthcare industry -- 1.3 Application of edge computing in smart healthcare systems -- 1.4 Challenges of using edge computing with IoMT-based system in smart healthcare system -- 1.5 The framework for edge-IoMT-based smart healthcare system |
|
1.6 Case study for the application of edge-IoMT-based systems enabled for the diagnosis of diabetes mellitus -- 1.6.1 Experimental results -- 1.7 Future prospects of edge computing for internet of medical things -- 1.8 Conclusions and future research directions -- References -- 2 Physical layer architecture of 5G enabled IoT/IoMT system -- 2.1 Architecture of IoT/IoMT system -- 2.1.1 Sensor layer -- 2.1.2 Gateway layer -- 2.1.3 Network layer -- 2.1.4 Visualization layer -- 2.2 Consideration of uplink healthcare IoT system relying on NOMA -- 2.2.1 Introduction -- 2.2.2 System model |
|
2.2.3 Outage probability for UL NOMA -- 2.2.3.1 Outage probability of x1 -- 2.2.3.2 Outage probability of X2 -- 2.2.3.3 Asymptotic -- 2.2.4 Ergodic capacity of UL NOMA -- 2.2.5 Numerical results and discussions -- 2.3 Conclusions -- References -- 3 HetNet/M2M/D2D communication in 5G technologies -- 3.1 Introduction -- 3.2 Heterogenous networks in the era of 5G -- 3.2.1 5G mobile communication standards and enhanced features -- 3.2.2 5G heterogeneous network architecture -- 3.2.3 Intelligent software defined network framework of 5G HetNets -- 3.2.4 Next-Gen 5G wireless network |
|
3.2.5 Internet of Things toward 5G and heterogenous wireless networks -- 3.2.6 5G-HetNet H-CRAN fronthaul and TWDM-PON backhaul: QoS-aware virtualization for resource management -- 3.2.7 Spectrum allocation and user association in 5G HetNet mmWave communication: a coordinated framework -- 3.2.8 Diverse service provisioning in 5G and beyond: an intelligent self-sustained radio access network slicing framework -- 3.3 Device-to-Device communication in 5G HetNets -- 3.4 Machine-to-Machine communication in 5G HetNets |
|
3.4.1 Machine-to-Machine communication in 5G: state of the art architecture, recent advances and challenges -- 3.4.2 Recent advancement in the Internet of Things related standard: oneM2M perspective -- 3.4.2.1 Advantages of oneM2M -- 3.4.2.2 OneM2M protocols -- 3.4.2.3 OneM2M standard platform: a unified common service-oriented communication framework -- 3.4.3 M2M traffic in 5G HetNets -- 3.4.4 Distributed gateway selection for M2M communication cognitive 5G5G networks -- 3.4.5 Algorithm for clusterization, aggregation, and prioritization of M2M devices in 5G5G HetNets |
| Summary |
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. |
| Subject |
Medical informatics.
|
|
Artificial intelligence -- Medical applications.
|
|
5G mobile communication systems.
|
|
Edge computing.
|
|
Internet of things.
|
|
Artificial intelligence.
|
|
Medical Informatics |
|
Cloud Computing |
|
Internet of Things |
|
Delivery of Health Care |
|
Artificial Intelligence |
|
Médecine -- Informatique.
|
|
Intelligence artificielle -- Applications en médecine.
|
|
Communications mobiles 5G.
|
|
Internet des objets.
|
|
Prestation de soins.
|
|
Intelligence artificielle.
|
|
artificial intelligence.
|
|
5G mobile communication systems
|
|
Artificial intelligence -- Medical applications
|
|
Edge computing
|
|
Internet of things
|
|
Medical informatics
|
| Added Author |
Bhoi, Akash Kumar.
|
| Other Form: |
Print version: 032390548X 9780323905480 (OCoLC)1268112824 |
| ISBN |
9780323906647 (electronic bk.) |
|
0323906648 (electronic bk.) |
|
9780323905480 |
|
032390548X |
| Standard No. |
AU@ 000071513165 |
|
UKMGB 020490060 |
|
