TY - GEN
T1 - CNN-Based Medical Device Design for the Smart Pillbox with Face Recognition
AU - Wu, Fan
AU - Lin, Yang Cheng
AU - Wu, You Hsun
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/10
Y1 - 2020/10
N2 - This study aims to assist elders with chronic diseases living in healthcare centers or a big family. In the era of AI, designers are not only to design product forms and functions, but the computer vision technique of AI can be used to help them. Based on the convolutional neural network (CNN) technology (as a supervised learning), three different types of optimizers of MobileNet V2 for training the best model accuracy, which is applied to a gerontechnological pillbox device with face recognition. In addition, the MobileNet V2 model proposed is imported into the JETSON edge machine that can identify different faces and then emit different sounds with its corresponding name and the quantity of medications. The smart pillbox device can improve the compliance and safety of elderly people when taking medicine.
AB - This study aims to assist elders with chronic diseases living in healthcare centers or a big family. In the era of AI, designers are not only to design product forms and functions, but the computer vision technique of AI can be used to help them. Based on the convolutional neural network (CNN) technology (as a supervised learning), three different types of optimizers of MobileNet V2 for training the best model accuracy, which is applied to a gerontechnological pillbox device with face recognition. In addition, the MobileNet V2 model proposed is imported into the JETSON edge machine that can identify different faces and then emit different sounds with its corresponding name and the quantity of medications. The smart pillbox device can improve the compliance and safety of elderly people when taking medicine.
UR - http://www.scopus.com/inward/record.url?scp=85099709938&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85099709938&partnerID=8YFLogxK
U2 - 10.1109/ICCST50977.2020.00125
DO - 10.1109/ICCST50977.2020.00125
M3 - Conference contribution
AN - SCOPUS:85099709938
T3 - Proceedings - 2020 International Conference on Culture-Oriented Science and Technology, ICCST 2020
SP - 607
EP - 611
BT - Proceedings - 2020 International Conference on Culture-Oriented Science and Technology, ICCST 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 International Conference on Culture-Oriented Science and Technology, ICCST 2020
Y2 - 30 October 2020 through 31 October 2020
ER -