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|a (OCoLC)1308798665
|z (OCoLC)1309047866
|z (OCoLC)1309049847
|z (OCoLC)1351462040
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|a R858
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|a 610.285
|2 23
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| 245 |
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|a 5G IoT and edge computing for smart healthcare
|h [electronic resource] /
|c edited by Akash Kumar Bhoi [and more].
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| 260 |
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|a [S.l.] :
|b Academic Press,
|c 2022.
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| 300 |
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|a 1 online resource
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| 336 |
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|a text
|2 rdacontent
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| 337 |
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|a computer
|2 rdamedia
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| 338 |
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|a online resource
|2 rdacarrier
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| 490 |
0 |
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|a Intelligent data centric systems
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| 505 |
2 |
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|a 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.
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| 505 |
0 |
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|a 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
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| 505 |
8 |
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|a 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
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8 |
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|a 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
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8 |
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|a 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
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|a 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
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| 650 |
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0 |
|a Medical informatics.
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| 650 |
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0 |
|a Artificial intelligence
|x Medical applications.
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| 650 |
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0 |
|a 5G mobile communication systems.
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| 650 |
|
0 |
|a Edge computing.
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| 650 |
|
0 |
|a Internet of things.
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| 650 |
|
6 |
|a M�edecine
|x Informatique.
|0 (CaQQLa)201-0103112
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| 650 |
|
6 |
|a Intelligence artificielle en m�edecine.
|0 (CaQQLa)201-0180593
|
| 650 |
|
6 |
|a Communications mobiles 5G.
|0 (CaQQLa)000313210
|
| 650 |
|
6 |
|a Internet des objets.
|0 (CaQQLa)000269177
|
| 650 |
|
7 |
|a 5G mobile communication systems
|2 fast
|0 (OCoLC)fst02009233
|
| 650 |
|
7 |
|a Artificial intelligence
|x Medical applications
|2 fast
|0 (OCoLC)fst00817267
|
| 650 |
|
7 |
|a Edge computing
|2 fast
|0 (OCoLC)fst02020291
|
| 650 |
|
7 |
|a Internet of things
|2 fast
|0 (OCoLC)fst01894151
|
| 650 |
|
7 |
|a Medical informatics
|2 fast
|0 (OCoLC)fst01014175
|
| 700 |
1 |
|
|a Bhoi, Akash Kumar.
|
| 776 |
0 |
8 |
|i Print version:
|z 032390548X
|z 9780323905480
|w (OCoLC)1268112824
|
| 856 |
4 |
0 |
|u https://sciencedirect.uam.elogim.com/science/book/9780323905480
|z Texto completo
|
