5G network slice for digital real-time healthcare system powered by network data analytics
In the wake of the COVID-19 pandemic, where almost the entire global healthcare ecosystem struggled to handle patients, it’s evident that the healthcare segment needs a virtual real-time digital support system. The recent advancements in technology have enabled machine-to-machine communication, enha...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2021-01-01
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| Series: | Internet of Things and Cyber-Physical Systems |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667345221000043 |
| _version_ | 1797742168890146816 |
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| author | Hemant Jain Vinay Chamola Yash Jain Naren |
| author_facet | Hemant Jain Vinay Chamola Yash Jain Naren |
| author_sort | Hemant Jain |
| collection | DOAJ |
| description | In the wake of the COVID-19 pandemic, where almost the entire global healthcare ecosystem struggled to handle patients, it’s evident that the healthcare segment needs a virtual real-time digital support system. The recent advancements in technology have enabled machine-to-machine communication, enhanced mobile broadband, and real-time biometric data analytics. These could potentially fulfill the requirements of an end-to-end digital healthcare system. For building such a system, there is also a need for a dedicated and specialized communication network. Such a system will not only support dynamic throughput, latency and payload but also provide guaranteed QoS (Quality of Service) at every instant. The motive of our study was to define an implementable low-level architecture for the digital healthcare system by using the 5G Network Slice that incorporates all these features. Best-in-class wearable devices will collect the biometric data and transmit it via the 5G network slice. Data analytics is then applied to the collected data to build a knowledge graph used for quick predictions and prescriptions. The architecture also keeps in mind the security and integrity aspects of healthcare data. |
| first_indexed | 2024-03-12T14:37:08Z |
| format | Article |
| id | doaj.art-501fcf7df7934284b89e1eb5a700e508 |
| institution | Directory Open Access Journal |
| issn | 2667-3452 |
| language | English |
| last_indexed | 2024-03-12T14:37:08Z |
| publishDate | 2021-01-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Internet of Things and Cyber-Physical Systems |
| spelling | doaj.art-501fcf7df7934284b89e1eb5a700e5082023-08-17T04:27:57ZengKeAi Communications Co., Ltd.Internet of Things and Cyber-Physical Systems2667-34522021-01-01114215G network slice for digital real-time healthcare system powered by network data analyticsHemant Jain0Vinay Chamola1Yash Jain2 Naren3Technology and Services strategy, Samsung Networks, Mumbai, 400063, IndiaDepartment of Electrical and Electronics Engineering & APPCAIR, BITS-Pilani, Pilani Campus, 333031, India; Corresponding author.Department of Electrical and Electronics Engineering, BITS-Pilani, Pilani Campus, 333031, IndiaDepartment of Electrical and Electronics Engineering, BITS-Pilani, Pilani Campus, 333031, IndiaIn the wake of the COVID-19 pandemic, where almost the entire global healthcare ecosystem struggled to handle patients, it’s evident that the healthcare segment needs a virtual real-time digital support system. The recent advancements in technology have enabled machine-to-machine communication, enhanced mobile broadband, and real-time biometric data analytics. These could potentially fulfill the requirements of an end-to-end digital healthcare system. For building such a system, there is also a need for a dedicated and specialized communication network. Such a system will not only support dynamic throughput, latency and payload but also provide guaranteed QoS (Quality of Service) at every instant. The motive of our study was to define an implementable low-level architecture for the digital healthcare system by using the 5G Network Slice that incorporates all these features. Best-in-class wearable devices will collect the biometric data and transmit it via the 5G network slice. Data analytics is then applied to the collected data to build a knowledge graph used for quick predictions and prescriptions. The architecture also keeps in mind the security and integrity aspects of healthcare data.http://www.sciencedirect.com/science/article/pii/S26673452210000435G network sliceSlice dimensioningDigital healthcareNetwork data analytics frameworkIoMT |
| spellingShingle | Hemant Jain Vinay Chamola Yash Jain Naren 5G network slice for digital real-time healthcare system powered by network data analytics Internet of Things and Cyber-Physical Systems 5G network slice Slice dimensioning Digital healthcare Network data analytics framework IoMT |
| title | 5G network slice for digital real-time healthcare system powered by network data analytics |
| title_full | 5G network slice for digital real-time healthcare system powered by network data analytics |
| title_fullStr | 5G network slice for digital real-time healthcare system powered by network data analytics |
| title_full_unstemmed | 5G network slice for digital real-time healthcare system powered by network data analytics |
| title_short | 5G network slice for digital real-time healthcare system powered by network data analytics |
| title_sort | 5g network slice for digital real time healthcare system powered by network data analytics |
| topic | 5G network slice Slice dimensioning Digital healthcare Network data analytics framework IoMT |
| url | http://www.sciencedirect.com/science/article/pii/S2667345221000043 |
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