Review Article Open Access

Adopting Intelligent Modelling to Trace Fault in Underground Optical Network: A Comprehensive Survey

Owusu Nyarko-Boateng1, Adebayo F. Adekoya2 and Benjamin A. Weyori1
  • 1 The University of Energy and Natural Resources, Ghana
  • 2 The University of Energy and Natural Resources, China

Abstract

Aiming at building new global optical network infrastructure optimized with fault tracing capabilities, light transmission monitoring, packets re-routing and reconfigurations require an intelligent optical transmission system. An intelligent approach to solve the increasingly complex problems, to enhance fault tracing in the underground optical network infrastructure need to be adopted. For over forty decades now, Optical Time Domain Reflectometry (OTDR) technology has been used to determine faults distance in Fiber Optic Cable (FOC). When it comes to underground optical networking, using OTDR measurements to trace fault on the earth surface takes much longer time since the device only measures the length of underground FOC from the optical transmitter to the point of the fault. Finding the exact spot of fault on earth is a complicated task due to several factors identified in this study. A comprehensive review of previous papers on how OTDR device and other scientific techniques have been used to trace faults in underground FOC were presented in this study. Due to the identified drawbacks in the OTDR to precisely trace fault in underground FOC networks, an intelligent fault tracing technique has been proposed to aid the process. The objective of this paper sought to conduct a comprehensive systematic review of previous studies on fault-finding techniques in underground FOC. To give a clear view of the available technologies used to conduct fault finding activities in underground FOC. The available intelligent systems and the possible future directions of tracing faults in FOC promptly and in a more economical manner.

Journal of Computer Science
Volume 16 No. 10, 2020, 1355-1366

DOI: https://doi.org/10.3844/jcssp.2020.1355.1366

Submitted On: 6 May 2020 Published On: 13 October 2020

How to Cite: Nyarko-Boateng, O., Adekoya, A. F. & Weyori, B. A. (2020). Adopting Intelligent Modelling to Trace Fault in Underground Optical Network: A Comprehensive Survey. Journal of Computer Science, 16(10), 1355-1366. https://doi.org/10.3844/jcssp.2020.1355.1366

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Keywords

  • Fiber Optics Cable
  • Artificial Intelligence
  • Predictive Model
  • Underground Optical Networks
  • Machine Learning and OTDR