Wheel Chair Movement through Eyeball Recognition Using Raspberry Pi

Abstract

When we think of how to help, whether financially or in another way, we often consider how we can provide assistance to those in need. We graduate students, on the other hand, have the advantage of being able to design a device that will benefit those less fortunate. Creating a positive impact on society is demonstrated by this initiative. There have been an increasing number of people who have been paralyzed in recent years. Paralysis describes a complete loss of power in a muscle group. In the most extreme scenario, a disabled individual would only be able to use his eyes. The project of constructing an eyeball movement-based wheelchair will be of the greatest help to these people with disabilities. This type of wheelchair would operate more accurately than earlier automated wheelchairs since noise from outside the environment can cause inaccuracy in voice-controlled wheelchairs and human effort is required to operate a head movement-based wheelchair. With our system, a person sitting in a wheelchair can stare directly at the camera and direct the wheelchair to the correct path by simply staring in the direction they desire. Using raspberry pi we implement this system. It consists of algorithms that let you operate your wheelchair. An Eyeball Localization method has been proposed to control wheelchair mobility. Several executional processes and an efficient system have been designed to reduce the costs and complexity of the algorithm. Through the serial port, an Open CV program analyzes camera signals and controls the motor attached to the Raspberry Pi CPU. As the technology is cost-effective, patients of different socioeconomic backgrounds can benefit from it. A wheelchair like this would have better accuracy than previous models.