0% Complete
فارسی
Home
/
پانزدهمین کنفرانس بین المللی فناوری اطلاعات و دانش
ML-based Optical Fibre Fault Detection in Smart Surveillance and Traffic Systems
Authors :
Rushil Patel
1
Sana Narmawala
2
Nikunjkumar Mahida
3
Rajesh Gupta
4
Sudeep Tanwar
5
Hossein Shahinzadeh
6
1- Institute of Technology, Nirma University
2- Institute of Technology, Nirma University
3- Institute of Technology, Nirma University
4- Institute of Technology, Nirma University
5- Institute of Technology, Nirma University
6- دانشگاه صنعتی امیرکبیر (پلیتکنیک تهران)
Keywords :
Optical Fibre،Smart City،Surveillance،Machine Learning،Fault Detection
Abstract :
It is evident that the intense transformation in the smart city structure has produced a demand for more optical fibre networks to facilitate the systems’ speedy communication for instance traffic control, surveillance, as well as IoT devices. Due to the nature of the optical fibre networks being very susceptible, and the slightest break or a bend can result in a major breakdown of operation; then, the ability to quickly identify the fault as well as rectify it is important in maintaining the efficiency of the systems. In this work, we propose a detailed workflow for fibre optic fault detection and classification using machine learning. We employ LightGBM, XGBoost, CatBoost, and AdaBoost machine learning models, along with OTDR data to categorize fault types. The process we adopt comprises enhancing the raw data to capture more of the signals quality before analyzing the data using these models for fault detection. Of all the models LightGBM was the best performing as it recorded an accuracy of 98.12% thereby making it to be the best model for this task. The use of key performance metrics such as accuracy, precision, recall, and F1-score along with confusion matrices, ROC curves on the graphs was done in order to measure the performance of the models accurately. Based on the performance of these models, a rational strategy in developing an intelligent solution for maintaining the operability and efficiency of smart city fibre optic networks is achieved.
Papers List
List of archived papers
Binary water stream algorithm: a new meta-heuristic optimization technique
Faezeh Rahimi Sebdani - Mehdi Nasri
کنترل کیفیت غیرمتمرکز مبتنی بر هوش ترکیبی در سیستمهای مشارکتی برخط
مهدیه طالب زاده - هاله امین طوسی - محمد اله بخش
روشی برای تشخیص مرحله پیشرفت آلزایمر در تصاویرFMRI مبتنی بر شبکه های عصبی چگال
فرساد زمانی بروجنی - عباس بهره دار
Dealing with Black-hole Attacks in Inter-vehicle Networks Using the Packet Delivery Rate Algorithm
Marzieh Sedighi - Mehdi Hamidkhani - Mostafa Sadeghi
تحویل بهینه جریان پخش زنده HTTP: یک رویکرد ترکیبی سرور- شبکه
فائزه امینی تهرانی - احمدرضا منتظرالقائم
Recommendation Systems in Smart Agriculture: Pathway to a well-designed system
Ahmad Nameni - Amir Ghafarian Daneshmand - Omid Mahdi Ebadati E
A Data-Efficient Approach to Solar Panel Micro-Crack Detection via Self-Supervised Learning
Alireza Akhavan safaei - Pegah Saboori - Reza Ramezani - Morteza Tavana
SDN-based Deep Anomaly Detection For Securing Cloud Gaming Servers
Mohammadreza Ghafari - Dr Seyed Mostafa Safavi Hemami
Distributed Learning Automata-based Algorithm for Finding K-Clique in Complex Social Networks
Mohammad Mehdi Daliri Khomami - Alireza Rezvanian - Ali Mohammad Saghiri - Mohammad Reza Meybodi
Presenting an Edge-based Air Quality Management System for Smart City Scenarios
Tina Samizadeh Nikoui - Ali Balador - Amir Masoud Rahmani - Hooman Tabarsaied
more
Samin Hamayesh - Version 41.3.1