Experimental Validation of RGB Dataset Analysis for Distribution System Operator Infrastructure Inspections
2024 IEEE 11th Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE 2024): Proceedings 2024
Diāna Gauče, Anna Litviņenko

This article focuses on experimentally validating techniques for analyzing red-green-blue (RGB) datasets in infrastructure inspections carried out by Distribution System Operators (DSOs). Given the increasing demand for efficient and precise inspection methods in the energy sector, leveraging RGB datasets presents a promising opportunity. The research investigates the effectiveness of RGB dataset analysis in identifying and evaluating critical infrastructure assets essential for DSO operations. The experimental validation underscores the potential of RGB data analysis as a valuable tool for improving infrastructure inspection procedures, streamlining maintenance schedules, and ensuring dependable energy distribution networks.


Keywords
data analytics, digital transformation, data-driven decision-making, artificial intelligence, geospatial information system, automation, Distribution System Operator, power system infrastructure
DOI
10.1109/AIEEE62837.2024.10586699
Hyperlink
https://ieeexplore.ieee.org/abstract/document/10586699

Gauče, D., Litviņenko, A. Experimental Validation of RGB Dataset Analysis for Distribution System Operator Infrastructure Inspections. In: 2024 IEEE 11th Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE 2024): Proceedings, Latvia, Valmiera, 31 May-1 Jun., 2024. Piscataway: IEEE, 2024, pp.110-116. ISBN 979-8-3315-2777-8. e-ISBN 979-8-3315-2776-1. ISSN 2689-7334. e-ISSN 2689-7342. Available from: doi:10.1109/AIEEE62837.2024.10586699

Publication language
English (en)
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