TY - JOUR
T1 - Cry Recognition for Infant Incubator Monitoring System Based on Internet of Things using Machine Learning
AU - Sutanto, Erwin
AU - Fahmi, Fahmi
AU - Shalannanda, Wervyan
AU - Aridarma, Arga
N1 - Funding Information:
The authors would like to thank the Ministry of Research and Technology (Kemenristek/BRIN) Government of Indonesia who supported this work by the Program Penelitian Kolaborasi Indonesia (PPKI) 2020 fund. The scheme was a collaboration between the Universitas Airlangga, Institut Technology of Bandung, and Universitas Sumatera Utara.
Publisher Copyright:
© 2020. International Journal of Intelligent Engineering and Systems. All Rights Reserved.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - Convolutional neural network (CNN)
KW - Infant incubator
KW - Internet of things (IoT)
KW - Machine learning
KW - Tensorflow
UR - http://www.scopus.com/inward/record.url?scp=85099566247&partnerID=8YFLogxK
U2 - 10.22266/IJIES2021.0228.41
DO - 10.22266/IJIES2021.0228.41
M3 - Article
AN - SCOPUS:85099566247
SN - 2185-310X
VL - 14
SP - 444
EP - 454
JO - International Journal of Intelligent Engineering and Systems
JF - International Journal of Intelligent Engineering and Systems
IS - 1
ER -