Motion based smart assistant for visually impaired people

Abstract

Objectives/Aim: The present paper deals with building a smart assistant with the aim of assisting the visually impaired people in mobility with confidence by realizing the nearby obstacles and also implement image processing techniques to recognize people. Methods: We use Raspberry Pi 4 which has increased computing performance and is interfaced to the picamera, GPS and GSM modules. Arduino pro mini with buzzer, ultrasonic sensors and vibration motors are used for obstacle detection. Certain libraries important for image processing are used such as OpenCV, Dlib, face detection (Haar cascades, HOG + Linear SVM, or CNNs), espeak for converting text to speech. Programming was implemented through Python and Arduino compiler. Findings: Analysis was carried out using the proposed system for the blind and visually impaired people who could move around comfortably with confidence and were also able to detect objects and recognize people. Hence the proposed system removes the use for the cumbersome white cane in exchange for small and handy modules which can be used in the form of wearables mounted on shoulders, hands and legs to detect the obstacles from multiple directions and provide for a comfortable wear. It was determined that the Raspberry pi 4 was incapable of running CNN detection for which ideally computer GPU was required, so HOG detection method was used instead. Application/Improvements: This project can be implemented mainly in the commercial field of helping visually impaired people with poor eyesight or being completely blind. Industrial applications can be devised and enhanced like robots and machineries along with Security, Identifying and Tracking.

Intelligent Environments and Assistive Technologies For Assisting Visually Impairment People: A Systematic Literature Review

“…Khan et al [77] developed a smart assistant designed to help visually impaired individuals in mobility by identifying nearby obstacles. The assistant makes use of an Arduino pro mini for obstacle detection, a task in which ultrasonic sensors are often involved.…”

“…Khan et al [77] developed a smart assistant for visually impaired individuals. The assistant is powered by Raspberry Pi 4 and uses an Arduino Pro Mini for obstacle detection, along with other components.…”

“…Khan et al [77] developed a smart assistant intended to assist VIPs in mobility by detecting nearby obstacles and employing image processing techniques for people recognition. The assistant, powered by Raspberry Pi 4, uses an Arduino pro mini for obstacle detection, along with other components.…”