Title: Tourism scene monitoring using mobile edge computing and business driven action learning

Authors: Hong Yu

Addresses: College of Management, Hunan City University, Yiyang, Hunan, China

Abstract: In order to improve the environment of domestic tourism scenes, enforce its monitoring means and strength, and improve its ability to respond to emergencies, the monitoring means of domestic tourism scenes under big data is discussed based on Mobile Edge Computing (MEC) and Business Driven Action Learning (BDAL). First, the concept and construction of edge computing are analysed, including tourist number monitoring, tourist density and the security of tourist scenes. And these monitoring data are processed in time to make a reasonable tourist diversion scheme; second, the BDAL is analysed to explore its function of data analysis and processing; finally, a tourism scene monitoring modal is constructed.

Keywords: edge computing; business-driven action learning; data analysis; tourism management; scene monitoring.

DOI: 10.1504/IJGUC.2022.124393

International Journal of Grid and Utility Computing, 2022 Vol.13 No.2/3, pp.282 - 290

Received: 06 Mar 2021
Accepted: 31 May 2021
Published online: 26 Jul 2022 *

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