Paper Title
Artificial Intelligence and Convolutional Neural Networks Optimized for Industrial Processes
Abstract
The aim of this scientific paper is an experimental of artificial intelligence techniques using deep learning and in
particular convolutional neural networks (CNN) to optimize industrial processes. An application is presented that is able to
recognize components within an electrical equipment and verify their state. At the same time, the application attempts to
identify the coding of industrial components in order to be able to construct an enrichment of the component information.
Using an optical character recognition system for detecting and reading the component coding, a search is conducted for the
technical specifications of the components. On this aspect, an innovative category prediction system is presented that can
recommend the best solution for possible modifications or changes in the event of component malfunctions or failures.
Keywords - Artificial Intelligence, Machine Learning, Deep Learning, CNN