TY - JOUR
T1 - Design of an IoT-based smart incubator that listens to the baby
AU - Fahmi, F.
AU - Shalannanda, W.
AU - Zakia, I.
AU - Sutanto, E.
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2020/12/28
Y1 - 2020/12/28
N2 - In the industrial era 4.0, domestic baby incubator producers are facing the challenge of free trade of foreign products that will compete in innovation with the application of IoT technology. One of the opportunities that arise consciously or unconsciously at the NICU (Neonatal Intensive Care Unit) unit in Hospitals, in general, is that there are no facilities for parents to monitor the baby's condition inside the incubator directly. The purpose of this research project is to build a prototype of an internet-based baby incubator monitoring system based on things equipped with various sensors that will send data to the server in real-Time and mobile apps for monitoring facilities for parents, including the voice of the baby. This study focused on how to develop baby incubators that can listen to baby's crying, capture the voice, and interpret it using artificial intelligence. More than 40 (forty) voice datasets were used and successfully classified into five possible terms of the baby's condition: burping, sleepy, hungry, uncomfortable, and pain by energy signal and spectrum analysis. The benefit of this research is as a driver of innovation for baby incubator products that will support the national medical devices manufacturing company.
AB - In the industrial era 4.0, domestic baby incubator producers are facing the challenge of free trade of foreign products that will compete in innovation with the application of IoT technology. One of the opportunities that arise consciously or unconsciously at the NICU (Neonatal Intensive Care Unit) unit in Hospitals, in general, is that there are no facilities for parents to monitor the baby's condition inside the incubator directly. The purpose of this research project is to build a prototype of an internet-based baby incubator monitoring system based on things equipped with various sensors that will send data to the server in real-Time and mobile apps for monitoring facilities for parents, including the voice of the baby. This study focused on how to develop baby incubators that can listen to baby's crying, capture the voice, and interpret it using artificial intelligence. More than 40 (forty) voice datasets were used and successfully classified into five possible terms of the baby's condition: burping, sleepy, hungry, uncomfortable, and pain by energy signal and spectrum analysis. The benefit of this research is as a driver of innovation for baby incubator products that will support the national medical devices manufacturing company.
UR - http://www.scopus.com/inward/record.url?scp=85098866390&partnerID=8YFLogxK
U2 - 10.1088/1757-899X/1003/1/012153
DO - 10.1088/1757-899X/1003/1/012153
M3 - Conference article
AN - SCOPUS:85098866390
SN - 1757-8981
VL - 1003
JO - IOP Conference Series: Materials Science and Engineering
JF - IOP Conference Series: Materials Science and Engineering
IS - 1
M1 - 012153
T2 - 2nd International Conference on Industrial and Manufacturing Engineering, ICI and ME 2020
Y2 - 3 September 2020 through 4 September 2020
ER -