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Vol. 32, No. 8(2), S&M2292

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Sensors and Materials
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Sensors and Materials, Volume 33, Number 6(1) (2021)
Copyright(C) MYU K.K.
pp. 1869-1881
S&M2580 Technical Paper of Special Issue
https://doi.org/10.18494/SAM.2021.3247
Published: June 1, 2021

Applying Internet of Things to Data Monitoring of Powered Wheelchairs [PDF]

Chien-Yu Lu, Chia-Liang Tseng, Wen-Yih Horng, Yu-Shan Chiu, Ching-Chou Tai, and Te-Jen Su

(Received December 30, 2020; Accepted April 1, 2021)

Keywords: Internet of Things, data monitoring, Raspberry Pi, RFID, QGIS

The aim of this study is to use the Internet of Things (IoT) for data monitoring of powered wheelchairs, which is divided into monitoring the position, tire wear, and battery charge level. Our system can be divided into two parts: Arduino UNO (an open-source microcontroller board; the word “uno” means “one” in Italian) and Raspberry Pi. Arduino UNO combines radio frequency identification (RFID) to read Electronic Product Code (EPC) tag information to establish the position information of powered wheelchairs. Raspberry Pi, through cooperation with the Quantum Geographic Information System (QGIS), establishes a coordinate activity map and monitors the tire wear of the powered wheelchair at any time, and uses a DC100 V LED dual display digital voltage meter head and external shunt to detect the lead-acid battery charge level of the powered wheelchair. Finally, a Microsoft Excel macro and Excel Visual Basic for Applications (VBA) are used to integrate the EPC tag information, tire wear, and lead-acid battery power consumption data and display them as real-time dynamic charts. The user can know the status of the wheelchair at any time, the user’s family can also know the operation status of an elderly user or one with limited mobility, and the user is informed in advance when the wheelchair needs to be adjusted.

Corresponding author: Te-Jen Su


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This work is licensed under a Creative Commons Attribution 4.0 International License.

Cite this article
Chien-Yu Lu, Chia-Liang Tseng, Wen-Yih Horng, Yu-Shan Chiu, Ching-Chou Tai, and Te-Jen Su, Applying Internet of Things to Data Monitoring of Powered Wheelchairs, Sens. Mater., Vol. 33, No. 6, 2021, p. 1869-1881.



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