Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Detection and Classification of Industrial Signal Lights for Factory Floors

Type de record:

paper
Créateur:
NilJakAlo
Éditeur:
arXiv
Hôte:avatar
Industrial manufacturing has developed during the last decades from a labor-intensive manual control of machines to a fully-connected automated process. The next big leap is known as industry 4.0, or smart manufacturing. With industry 4.0 comes increased integration between IT systems and the factory floor from the customer order system to final delivery of the product. One benefit of this integration is mass production of individually customized products. However, this has proven challenging to implement into existing factories, considering that their lifetime can be up to 30 years. The single most important parameter to measure in a factory is the operating hours of each machine. Operating hours can be affected by machine maintenance as well as re-configuration for different products. For older machines without connectivity, the operating state is typically indicated by signal lights of green, yellow and red colours. Accordingly, the goal is to develop a solution which can measure the operational state using the input from a video camera capturing a factory floor. Using methods commonly employed for traffic light recognition in autonomous cars, a system with an accuracy of over 99% in the specified conditions is presented. It is believed that if more diverse video data becomes available, a system with high reliability that generalizes well could be developed using a similar methodology. Published at Proc International Conference on Intelligent Systems and Computer Vision, ISCV, Fez, Morocco, 9-11 June 2020

Visit

doi.orgarxiv.org

Tasks

computer visionimage classification

Tags

Computer Vision and Pattern Recognition (cs.CV)FOS: Computer and information sciencesFOS: Computer and information sciences

Licenses

arXiv.org perpetual, non-exclusive licensehttp://arxiv.org/licenses/nonexclusive-distrib/1.0/

Similaires

An Indian Roads Dataset for Supported and Suspended Traffic Lights DetectionMasculine voices signal men's threat potential in forager and industrial societiesjadebc/washb-floors-publicGPR Signal Characterization for Automated Landmine and UXO Detection Based on Machine Learning TechniquesHarmonized Nighttime Lights for Africa (Vintage)Human Lights version 1 Human Lights version 1

An Indian Roads Dataset for Supported and Suspended Traffic Lights Detection

Autonomous vehicles are growing rapidly, in well-developed nations like America, Europe, and China.

Masculine voices signal men's threat potential in forager and industrial societies

Humans and many non-human primates exhibit large sexual dimorphisms in vocalizations and vocal anato

jadebc/washb-floors-public

Household finished flooring and soil-transmitted helminth and Giardia infections among children in r

GPR Signal Characterization for Automated Landmine and UXO Detection Based on Machine Learning Techniques

Landmine clearance is an ongoing problem that currently affects millions of people around the world.

Harmonized Nighttime Lights for Africa (Vintage)

A harmonized series of annual nighttime lights, made temporally consistent across the DMSP-

Human Lights version 1 Human Lights version 1

Satellite nighttime lights open new opportunities for economic research. The data is objective and s