Open AccessResearch on failure rate of self-service payment terminal of power supply company based on cloud computing
Author(s) -
Ming Xu,
Fei Song,
Yan Sun,
Shan Lang,
Long Wen
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/680/1/012007
Subject(s) - cloud computing , terminal (telecommunication) , computer science , payment , software deployment , scalability , service (business) , big data , reliability (semiconductor) , failure rate , data as a service , payment service provider , reliability engineering , computer security , power (physics) , database , operating system , computer network , business , engineering , world wide web , physics , marketing , quantum mechanics
With the continuous development of power companies, the load on the user side continues to diversify, the traditional payment methods in the power system are constantly updated, and the scale of self-service payment terminals has been fully expanded. However, as the scale of self-service payment terminals becomes larger and terminal equipment functions become more abundant, the failure rate of terminal equipment is also on the rise. Cloud computing can provide a large number of low-cost computing and storage resources, and has the characteristics of easy deployment and strong scalability, which can meet the software and hardware needs of big data analysis. Therefore, the effective integration of cloud computing and big data technology and the use of their respective advantages have important practical significance in the big data analysis of equipment failure. Completing the prediction of the failure rate of the terminal equipment according to the designed big data analysis framework will help to arrange the maintenance plan of the terminal equipment reasonably and improve the reliability of the power self-service payment terminal.