ML Based Risk Analysis and Route Prediction for Optical Fibre Link Network

Abstract

Predicting the risk of an optical fibre link prior to its deployment is a step of capital importance for an optimised design of the network. In this paper, we have tried to expand the power of abundant data into the field of optical fibre networks by predicting the probable risk post establishment of a candidate path based on its physical factors such as road density, obstruction density and water density, etc. for identifying the fibre implementation risk and achieving a better route.