CNN Based Personal Assistive System for Deaf-Blind

Deaf-Blindness restricts a person's ability to learn about their environment, making unaided navigation, object recognition, obstacle avoidance, and reading tasks difficult. As there is now relatively little available to visually impaired people, there is a need to deploy technology that supports them in their everyday chores. Available systems, such as Braille devices and Screen Reading software, assist visually impaired people in reading and acquiring access to various devices, but such technologies become ineffective when the blind want to execute fundamental activities including perceiving the world before him, such as people or objects. The Raspberry Pi 3 Model has been utilized to display the functionality of the suggested prototype advantages of tiny size, low cost and ease of integration. The aim of the proposed device is to develop a personal assistant system for deaf-blind people to help identify faces of people and objects in terms of Morse code. The current set up is designed to deaf-blind to live independent. The proposed device has been designed with CNN algorithm which is a major part of deep learning to identify the objects. The resultant output is produced through vibrators and morse code as well.