Enhanced Mobility Aid for the Visually Impaired: An Ultrasonic Sensor and Arduino-Based Smart Walking Stick

Shahzor Memon; Mirza Muhammad Aamir; Sadiq Ur Rehman; Halar Mustafa; Muhammad Shakir Sheikh

doi:10.36561/ING.28.3

Authors

Shahzor Memon Hamdard University, Pakisán https://orcid.org/0009-0008-8867-7070
Mirza Muhammad Aamir Hamdard University, Pakistán https://orcid.org/0009-0009-5304-1950
Sadiq Ur Rehman Hamdard University, Pakistán https://orcid.org/0000-0002-6308-450X
Halar Mustafa Hamdard University, Pakistán https://orcid.org/0000-0002-7021-5010
Muhammad Shakir Sheikh Hamdard University, Pakistán https://orcid.org/0009-0005-5902-6461

DOI:

https://doi.org/10.36561/ING.28.3

Keywords:

Ultrasonic sensor, Arduino ATmega328 Microcontroller, Mobility aid, Visually Impaired Person, Alarm system

Abstract

This study introduces a smart walking stick for the blind and visually impaired that uses ultrasonic sensors with Arduino and Raspberry Pi. The World Health Organization estimates that 37 million people worldwide are blind. People who are blind or visually impaired frequently rely on assistance from outside sources, which may come in the form of humans, dogs that have been trained, or specialized technological gadgets that play the role of decision-making support systems. We were then inspired to create a smart walking stick in order to get around these restrictions. In order to achieve this, we fitted the stick with ultrasonic sensors at strategic locations that activated the buzzer sound while giving the user information about the surroundings. Our proposal was for a low-cost, lightweight device that uses a microcontroller to interpret signals and emit beeps to notify the visually impaired individual of any obstacles, water, or dark places. The system consists of obstacle and moisture detection sensors that receive, process, and send signals to the alarm system, which then warns the user to take action. The system was conceived and programmed in C, tested for accuracy, and checked by a visually challenged individual. Our technology can identify obstructions within around 2 meters of the user.

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