SMCS: Mobile Model Oriented to Cloud for the Automatic Classification of Environmental Sounds

  • María José Mora-Regalado
  • Omar Ruiz-VivancoEmail author
  • Alexandra Gonzalez-Eras
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1066)


This paper presents SMCS, a cloud-oriented mobile system model that uses a Convolutional Neural Network for the automatic classification of environmental sounds in real time. The model comprises an architectural schema with its corresponding deployment scheme in Google cloud services provider. Finally, the validation protocol of SMCS is applied in two experiments using respectively the base of free sounds FSDkaggle2018 and a selection of warning sounds extracted from the same sound base. The results of the validation of the model are promising with high values of precision in the classification of sounds, demonstrating that the SMCS model is expected to be a point of reference for the development of sound analysis systems, contributing to improving the quality of life of people with Hearing Impairment.


Hearing impairment Cloud Computing Mobile system Convolutional neural network FSDkaggle2018 


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Universidad Técnica Particular de LojaLojaEcuador

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