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Prototyping An Autonomous Eye-Controlled System (AECS) using Raspberry-Pi on Wheelchairs

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Jayanth Thota, Priyanka Vangali, Xiaokun Yang

Jayanth Thota, Priyanka Vangali and Xiaokun Yang. Prototyping An Autonomous Eye-Controlled System (AECS) using Raspberry-Pi on Wheelchairs. International Journal of Computer Applications 158(8):1-7, January 2017. BibTeX

	author = {Jayanth Thota and Priyanka Vangali and Xiaokun Yang},
	title = {Prototyping An Autonomous Eye-Controlled System (AECS) using Raspberry-Pi on Wheelchairs},
	journal = {International Journal of Computer Applications},
	issue_date = {January 2017},
	volume = {158},
	number = {8},
	month = {Jan},
	year = {2017},
	issn = {0975-8887},
	pages = {1-7},
	numpages = {7},
	url = {},
	doi = {10.5120/ijca2017912853},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


In order to help physically disabled persons to make their life independent, this paper proposes an autonomous eye controlled system (AECS) on wheelchairs. In this work, several OpenCV image processing algorithms are employed to track the eye motion to coordinate the wheelchair moving left, right, and straight forward. We use the Raspberry-Pi B+ board as the system center to process the images and control the motors via GPIO. Experimental results show that the ACES system can be effectively used in the prototype, and outperforms the hand gesture controlled system by 25% processing latency reduction.


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Eye controlled system, gesture controlled system, image processing, OpenCV, Raspberry-Pi