Eye Controlled Robotic Chair with Night Vision Camera - Harish Babu, G; N. Venkatram, Dr (International Journal of Engineering and Technology, 2018)
According to Census 2011, in India the population is 121 Cr, from the aggregate residents 2.68 Cr individuals are impaired i.e 2.21 percent of the aggregate residents. From the 2.68 Cr impaired individuals 20 percent of the people disability in movement. Our project is an attempt to make lives of the people suffering from this phenomenon simple. In this framework controlling of wheel chair is depends upon the movements of patient’s Eye [1].  A camera is placed before the user, to catch the picture of the eye & footmarks the locale of eye pupil.  Camera used here is Night vision camera which works during night time and as well as daytime and will also work during low lightings. As per the position of eye pupil, wheel chair will be coordinated to move left, appropriate, forward and in reverse. The previous algorithms which are developed for this type of project doesn’t support for the people with squint eye and supports only for the people with 2 perfect pupils, and those algorithms are works only in clear light conditions but this project supports for the people with squint eye as well as people with 2 perfect pupils and works during low lightings. The person can stop the chair by closing his eyes whenever he needs. Moreover, a ultrasonic sensor is ascended in front, so that it can recognize the snags and naturally stop the wheel chair. A GPS module is inserted which finds the location of the wheel chair. A GSM module is inserted which sends the messages in case of emergency situations.  This project provides an option called voice module which is inserted and works based on the commands of the patients.
Keywords: Camera; GPS; GSM; Image Processing; Open Computer vision Library; Python; Raspberry Pi; Wheel chair.