Research and Application of 5G Edge AI in Medical Industry
21st IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2022
; : 1462-1466, 2022.
Article
in English
| Scopus | ID: covidwho-2304582
ABSTRACT
With the development of 5G and AI technology, the infectious virus detection framework system based on the combination of 5G MEC and medical sensors can effectively assist in the intelligent detection and control of influenza viruses such as COVID-19. Employing the edge computing and 5G+MEC model, the virus AI model is trained for the collected influenza virus data. Then the virus AI model can be used to evaluate the virus patients on the local edge computing service platform. Therefore, this paper introduces an algorithm and resource allocation, which uses 5G functions (especially, low latency, high bandwidth, wide connectivity, and other functions) to achieve local chest X-ray or CT scan images to detect COVID-19. Meanwhile, this paper also compares the computational efficiency of different algorithms in the 5G edge AI-based infectious virus detection framework, in this way to select the best algorithm and resource allocation. © 2022 IEEE.
Artificial Intelligence; Edge Computing; Fog Computing; Internet of Things; Medical Detection; 5G mobile communication systems; Computational efficiency; Computerized tomography; Resource allocation; Viruses; AI Technologies; Detection framework; Infectious virus; Influenza virus; Medical industries; Research and application; Resources allocation; Virus detection
Full text:
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Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
21st IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2022
Year:
2022
Document Type:
Article
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