Cry Recognition for Infant Incubator Monitoring System Based on Internet of Things using Machine Learning

Erwin Sutanto, Fahmi Fahmi, Wervyan Shalannanda, Arga Aridarma

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

With the current technology trend of IoT and Smart Device, there is a possibility for the improvement of our infant incubator in responding to the real baby’s condition. This work is trying to see that possibility. First is by analyzing of open baby voice database. From there, a procedure to find out baby cry classification will be explained. The approach was starting with an analysis of sound’s power from that WAV files before going further into the 2D pattern, which will have features for the machine learning. From this work, around 85% accuracy could be achieved. Then together with sensors, it would be useful for infant incubator’s innovation by utilizing this proposed configuration.

Original languageEnglish
Pages (from-to)444-454
Number of pages11
JournalInternational Journal of Intelligent Engineering and Systems
Volume14
Issue number1
DOIs
Publication statusPublished - 2021

Keywords

  • Convolutional neural network (CNN)
  • Infant incubator
  • Internet of things (IoT)
  • Machine learning
  • Tensorflow

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