Future Trends of IoT, 5G Mobile Networks, and AI: Challenges, Opportunities, and Solutions


Ji Su Park, Jong Hyuk Park, Journal of Information Processing Systems Vol. 16, No. 4, pp. 743-749, Aug. 2020  

10.3745/JIPS.03.0146
Keywords: Artificial intelligence, Internet of Things, machine vision, 5G Mobile Network
Fulltext:

Abstract

Internet of Things (IoT) is a growing technology along with artificial intelligence (AI) technology. Recently, increasing cases of developing knowledge services using information collected from sensor data have been reported. Communication is required to connect the IoT and AI, and 5G mobile networks have been widely spread recently. IoT, AI services, and 5G mobile networks can be configured and used as sensor-mobile edgeserver. The sensor does not send data directly to the server. Instead, the sensor sends data to the mobile edge for quick processing. Subsequently, mobile edge enables the immediate processing of data based on AI technology or by sending data to the server for processing. 5G mobile network technology is used for this data transmission. Therefore, this study examines the challenges, opportunities, and solutions used in each type of technology. To this end, this study addresses clustering, Hyperledger Fabric, data, security, machine vision, convolutional neural network, IoT technology, and resource management of 5G mobile networks.


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Cite this article
[APA Style]
Park, J. & Park, J. (2020). Future Trends of IoT, 5G Mobile Networks, and AI: Challenges, Opportunities, and Solutions. Journal of Information Processing Systems, 16(4), 743-749. DOI: 10.3745/JIPS.03.0146.

[IEEE Style]
J. S. Park and J. H. Park, "Future Trends of IoT, 5G Mobile Networks, and AI: Challenges, Opportunities, and Solutions," Journal of Information Processing Systems, vol. 16, no. 4, pp. 743-749, 2020. DOI: 10.3745/JIPS.03.0146.

[ACM Style]
Ji Su Park and Jong Hyuk Park. 2020. Future Trends of IoT, 5G Mobile Networks, and AI: Challenges, Opportunities, and Solutions. Journal of Information Processing Systems, 16, 4, (2020), 743-749. DOI: 10.3745/JIPS.03.0146.