Investigating How the Cloud Computing Transforms the Development of Industries

被引:15
作者
Hung, Yu-Hsin [1 ]
机构
[1] Natl Yunlin Univ Sci & Technol, Dept Ind Engn & Management, Touliu 64002, Yunlin, Taiwan
关键词
Cloud computing; machine learning; education as a service (EaaS); logistics as a service (LaaS); manufacturing as a service (MaaS); VALUE CO-CREATION; BIG DATA; SERVICE LOGIC; SECURITY; INTERNET; MODELS; THINGS; CHALLENGES; MANAGEMENT; LOGISTICS;
D O I
10.1109/ACCESS.2019.2958973
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The Internet of Things (IoT) transforms many fields, including the educational, logistics, and manufacturing industries. The IoT is an internet framework whereby a large number of devices or equipment are connected and synchronized using gateways, third-party technologies, and software in machine-to-machine and cloud computing networks. With the flourishing development of IoT, cloud computing plays an essential role in its application layer. Cloud computing technology has been widely applied in various industries and developed as particular cloud computing types: education as a service (EaaS), logistics as a service (LaaS), and manufacturing as a service (MaaS). The applicability of cloud computing in various industries has attracted significant attention from researchers and professionals. This study investigated the technical trends of emerging cloud computing technologies and surveyed 3,697 cloud computing-related studies from 2010 to 2019. The findings indicate that intelligence and automation are the core issues that drive research on cloud computing. The main types of research are critical review, system design, and systematic analysis. Cloud computing services (e.g., XaaS, EaaS, LaaS, MaaS) are related to big data, analytical technologies, service orientation, and IoT. This study applied machine-learning algorithms to analyze educational, logistic, and manufacturing data and yielded results with more than 90% accuracy and AUC. This study used various devices such as laptops, tablets, and smartphones to configure and review machine-learning models using third-party cloud platforms, which are infinitely scalable and flexible for data analytics, thereby allowing users to make quicker predictions and decisions focused on business needs.
引用
收藏
页码:181505 / 181517
页数:13
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