ITEGAM-JETIA (Apr 2024)

Detection of traffic accidents using artificial intelligence

  • Jesus Gerardo Ávila Sánchez,
  • Francisco Eneldo López Monteagudo,
  • Francisco Javier Martinez Ruiz,
  • Leticia del Carmen Ríos Rodríguez

DOI
https://doi.org/10.5935/jetia.v10i46.1109
Journal volume & issue
Vol. 10, no. 46

Abstract

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This article analyzes different architectures with which a neural network can be developed using computer vision with the objective of detecting traffic accidents. For the development of the software, the Java Script programming language was used, reaching the conclusion that the best architecture to use is a Convolutional Neural Network since it has the capabilities of detecting features within the images. At the same time, a database was developed with the necessary characteristics for the functioning of the neural network.