A Sign Language Control Based ATM Access System for the Blind Using AI/ML

In Today’s World, about 285 million people are visually impaired worldwide: 39 million are blind and 246 million have low vision (severe or moderate visual impairment) preventable causes are as high as 80% of the total global visual impairment burden. Globally, uncorrected refractive errors are the main cause of visual impairment. Cataracts are the leading cause of blindness 65% of visually impaired, and 82% of blind people are over 50 years of age, although this age group comprises only 20% of the world population. Blindness can be classified into 3 types, Complete blindness, Night blindness, and Color blindness. The main problems faced by blind people: during financial transactions especially in ATMs. In the existing ATMs, Braille is inscribed on the keypad to facilitate blind. But, What if people don't know Braille, or how to insert a card? The friend accompanying him might get to know the password or someone else can come to know of his pin number. A stranger might try to help the blind win the trust and rob him. So, we propose to design and develop a safer and more secure ATM accessing system for the blind.