Industrial Smart Asset Management for Power Services: Perspectives in Big Data

Sekoboto M.*, Poolo S.**, Kikawa C. R.***, Sematimba A.****, Ntirampeba D.*****
*-** The Da Vinci Institute, Lethabong, South Africa.
*** Department of Economics and Statistics, Kabale University, Kabale, Uganda.
**** Department of Mathematics, Gulu University, Uganda.
***** Department of Mathematics and Statistics, Namibia University of Science and Technology, Windhoek, Namibia.
Periodicity:July - December'2021
DOI : https://doi.org/10.26634/jcc.8.2.16475

Abstract

This study explores and discusses upcoming encounters with new technologies in line with big data. Power utilities collect large amounts of data. However, due to their large size and the ambiguity associated with it, they are rarely used. Condition monitoring of assets collects huge amounts of data during routine operations. The question "How to get information from a huge amount of data?" and the notion of "data-rich and information devoid" has faced significant resistance from analytics experts with the advent of support vector machines. Along with new technologies such as the Internet of Things (IoT), big data analytics will be actively used in power utilities. This study assesses the issues and points out ways to address them through paths and strategies to make asset management practices smarter for future generations.

Keywords

Smart Asset Management, Electrical Utilities, Big Data, Data Mining.

How to Cite this Article?

Sekoboto, M., Poolo, S., Kikawa, C. R., Sematimba, A., and Ntirampeba, D. (2021). Industrial Smart Asset Management for Power Services: Perspectives in Big Data. i-manager’s Journal on Cloud Computing, 8(2), 23-32. https://doi.org/10.26634/jcc.8.2.16475

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