Browse > Article
http://dx.doi.org/10.9728/dcs.2018.19.8.1507

Research of Smart Integrated Control Board Function Improvement for Personal Electric Wheelchair's Safe Driving  

Kim, Jinsul (School of Electronics and Computer Engineering, Chonnam National University)
Cho, Young-Bin (School of Electronics and Computer Engineering, Chonnam National University)
Publication Information
Journal of Digital Contents Society / v.19, no.8, 2018 , pp. 1507-1514 More about this Journal
Abstract
The purpose of this study was to propose a functional improvement solution of integrated control board for safe driving of Smart electric wheelchair for a single person. In the case of existing electric wheelchair products in Korea and elsewhere, safety-related functions or devices are not included in many cases. Therefore, the incidence of electric wheelchair-related accidents is continuously increasing in the current situation in which the elderly and the disabled people have been continuously increased. However, currently only high and middle-priced products are equipped with basic safety devices in electric wheelchairs, so low-priced products require safety related functions. Therefore, sensing obstacles that the user can not recognize while moving an electric wheelchair and detecting automatically the terrain change to control the motor by developing a smart control platform. This provides an integrated control board that can be applied to various electric wheelchairs for more stable driving.
Keywords
Gyro Sensor; Electric Wheelchair Control System; ZigBee Communication; I2C Communication; Acceleration Sensor;
Citations & Related Records
연도 인용수 순위
  • Reference
1 H. S. Jung,; Survey on the use of motorized wheelchair(electric wheelchair, electric scooter), KCA Report, November, 2015; pp. 1-3.
2 Cheong, P.; Ka-Fai Chang.; Ying-Hoi Lai.; Sut-Kam Ho.; Iam-Keong Sou.; Kam-Weng Tam. A ZigBee-based wireless sensor network node for ultraviolet detection of flame. Industrial Electronics, IEEE. 2011. 58, 5271-5277.   DOI
3 Torfs.; Tom.; et al. Low power wireless sensor network for building monitoring. Sensors Journal, IEEE. 2013, 13, 909-915.   DOI
4 Gorlatova.; Maria.; Aya Wallwater.; Gil Zussman. Networking low-power energy harvesting devices: Measurements and algorithms. Mobile Computing, IEEE. 2013, 12, 1853-1865.   DOI
5 Farahani.; Shahin. ZigBee wireless networks and transceivers. Newnes, 2011.
6 Liang.; Chieh-Jan Mike.; et al. Surviving wi-fi interference in low power zigbee networks. Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems. ACM, Zurich, Switzerland, 3-5 November 2010; pp. 309-322.
7 H. J. Kim.; H. W. Choi.; S. P. Hong.; A Study on Travel Time Prediction of the Interrupted Traffic Flow using Kalman filter Algorithm, 18th Yooshin technical bulletin, pp. 82-85