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Enabling Predictive and Preventive Maintenance using IoT and Big Data in the Telecom Sector

Mahmood, Tahir; Munir, Kamran


Tahir Mahmood

Kamran Munir
Associate Professor in Data Science


Telecom sector has always been working hard to improve network quality to satisfy end user services. Fixing telecom network errors (hardware and software) precisely and quickly is a main factor to improve quality of services. Telecom operators are spending a lot of budget on ad hoc maintenance to fix these errors. This paper presents a framework using internet of things (IoT) and big data to enable predictive and preventive maintenance, which have been applied in the telecom sector. A telecom network consists of radio nodes, transport network, switching centres and civil infrastructure; and in this paper, focus is on the maintenance of Radio Access Network (RAN). A challengeable task for telecom operators has been to maintain radio nodes as these are installed on different locations. This framework for predictive maintenance is modelled using active and historical data from telecom equipment as well as data collected from IoT devices and sensors. The major benefit of implementing this framework has been a control on the time and cost of the maintenance by pre-planning maintenance activities and related budget.

Start Date May 7, 2020
Publication Date May 8, 2020
ISBN 9789897584268
APA6 Citation Mahmood, T., & Munir, K. (2020). Enabling Predictive and Preventive Maintenance using IoT and Big Data in the Telecom Sector.


Paper-IoTBDS-2020 Camera Ready KM (249 Kb)


Copyright Statement
Copyright 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved. This article is made available under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license.

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