Data-Driven Surveillance of Internet Usage Using a Polynomial Profile Monitoring Scheme

Unarine Netshiozwi, Ali Yeganeh, Sandile Charles Shongwe () and Ahmad Hakimi
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Unarine Netshiozwi: Department of Mathematical Statistics and Actuarial Science, Faculty of Natural and Agricultural Sciences, University of the Free State, Bloemfontein 9301, South Africa
Ali Yeganeh: Department of Mathematical Statistics and Actuarial Science, Faculty of Natural and Agricultural Sciences, University of the Free State, Bloemfontein 9301, South Africa
Sandile Charles Shongwe: Department of Mathematical Statistics and Actuarial Science, Faculty of Natural and Agricultural Sciences, University of the Free State, Bloemfontein 9301, South Africa
Ahmad Hakimi: Department of Industrial Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj 0098, Iran

Mathematics, 2023, vol. 11, issue 17, 1-23

Abstract: Control charts, which are one of the major tools in the Statistical Process Control (SPC) domain, are used to monitor a process over time and improve the final quality of a product through variation reduction and defect prevention. As a novel development of control charts, referred to as profile monitoring, the study variable is not defined as a quality characteristic; it is a functional relationship between some explanatory and response variables which are monitored in such a way that the major aim is to check the stability of this model (profile) over time. Most of the previous works in the area of profile monitoring have focused on the development of different theories and assumptions, but very little attention has been paid to the practical application in real-life scenarios in this field of study. To address this knowledge gap, this paper proposes a monitoring framework based on the idea of profile monitoring as a data-driven method to monitor the internet usage of a telecom company. By definition of a polynomial model between the hours of each day and the internet usage within each hour, we propose a framework with three monitoring goals: (i) detection of unnatural patterns, (ii) identifying the impact of policies such as providing discounts and, (iii) investigation of general social behaviour variations in the internet usage. The results shows that shifts of different magnitudes can occur in each goal. With the aim of different charting statistics such as Hoteling T 2 and MEWMA, the proposed framework can be properly implemented as a monitoring scheme under different shift magnitudes. The results indicate that the MEWMA scheme can perform well in small shifts and has faster detection ability as compared to the Hoteling T 2 scheme.

Keywords: control chart; internet usage monitoring; profile monitoring; statistical process control (SPC); telecom company (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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