CNN-Based Medical Device Design for the Smart Pillbox with Face Recognition

Fan Wu, Yang Cheng Lin, You Hsun Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - 2020 International Conference on Culture-Oriented Science and Technology, ICCST 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages607-611
Number of pages5
ISBN (Electronic)9781728181387
DOIs
Publication statusPublished - 2020 Oct
Event2020 International Conference on Culture-Oriented Science and Technology, ICCST 2020 - Beijing, China
Duration: 2020 Oct 302020 Oct 31

Publication series

NameProceedings - 2020 International Conference on Culture-Oriented Science and Technology, ICCST 2020

Conference

Conference2020 International Conference on Culture-Oriented Science and Technology, ICCST 2020
Country/TerritoryChina
CityBeijing
Period20-10-3020-10-31

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Engineering (miscellaneous)
  • Cognitive Neuroscience
  • Sensory Systems
  • Cultural Studies

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