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S&M2227 Research Paper of Special Issue https://doi.org/10.18494/SAM.2020.2632 Published: May 31, 2020 Development of Smart Pillbox Using 3D Printing Technology and Convolutional Neural Network Image Recognition [PDF] Kun-Li Tsai, Ben-Yi Liau, Yu-Ming Hung, Gwo-Jeng Yu, and Yao-Chin Wang (Received September 25, 2019; Accepted March 24, 2020) Keywords: smart pillbox, 3D printing, embedded system, image recognition, convolution neural network (CNN)
Safety in taking medicine is important in health care. In this study, we propose a complete concept of an active smart pillbox, which comprises a main control unit, a pill dispenser unit, and an application software (app) for the automatic dispensing of medicine. The smart pillbox employs convolutional neural network image recognition and 3D printing technology. We adopt an Arduino-based platform to control the rotation and stopping of the motor to dispense the required quantity of pills as the first step towards a fully automated process. A smartphone can be connected to the smart pillbox by Bluetooth and be used to set the parameters of the system. This pillbox can be used at home and allows users to set the medication time and pill type from their smartphone using an app. Moreover, it can remind users to take their medicine. The device is very promising for use in home care and clinical practice.
Corresponding author: Yao-Chin WangThis work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Kun-Li Tsai, Ben-Yi Liau, Yu-Ming Hung, Gwo-Jeng Yu, and Yao-Chin Wang, Development of Smart Pillbox Using 3D Printing Technology and Convolutional Neural Network Image Recognition, Sens. Mater., Vol. 32, No. 5, 2020, p. 1907-1912. |