Clasificación de tipos de cables de conexión de fibra óptica a través de técnicas de visión artificial

Abstract

Abstract:Optical fiber is a more efficient and reliable transmission measure for long-distance data transfer in telecommunications and network infrastructure. However, as fiber optic networks become more complex and extensive, tools need to be developed to simplify their management, maintenance and learning. The precise classification of different types of fiber optic connection cables is critical to ensuring efficient network deployment and maintenance. Artificial vision techniques offer a promising solution to automate the process of classifying fiber optic cables. The development of an automated fiber optic cable classification system presents a great challenge, but it can also improve operational efficiency in communications network management, reduce costs and minimize human errors. An agile methodology such as KDD will be used in the analysis and development process, this work is divided into five chapters, focusing on artificial vision techniques for object classification, design tools for classification systems, data acquisition and processing techniques, image classification methods and algorithms, and system implementation. Research is crucial for innovation and the advancement of knowledge, enabling companies to improve their services and processes, ultimately achieving the overall goal.