AI-based detection of potholes ahead of a visually impaired person using ultrasonic sensors array and camera for blind navigation

Hamed, Hamed and Khan, Md. Raisuddin (2024) AI-based detection of potholes ahead of a visually impaired person using ultrasonic sensors array and camera for blind navigation. In: ICOM 2024, 13-14 August 2024, Kuala Lumpur.

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Abstract

Visually impaired individuals usually depend on assistive devices like white canes, frequently equipped with ultrasonic sensors, for navigation. However, these devices face significant limitations, particularly in detecting specific hazards such as potholes and deep trenches on walkways. This gap in functionality increases the risk of accidents and impedes safe, independent navigation for the visually impaired. The research developed a prototype of a blind assistive system equipped with an array of ultrasonic sensors and a Raspberry Pi integrated with Firebase for IoT capabilities. AI models, trained on the collected datasets of road images and ultrasonic sensor readings, were deployed on the Raspberry Pi. Testing in real-world scenarios was conducted to validate the prototype's effectiveness. The results showed that the AI model successfully detected potholes with an accuracy of 93%. The prototype could detect both large and small potholes using ultrasonic sensors and a camera but faced challenges in cases where potholes were filled with water or in complex environments.

Item Type:	Proceeding Paper (Plenary Papers)
Uncontrolled Keywords:	Blind Navigation, Pothole Detection, Artificial Intelligence, Assistive Devices, Wearable Technology
Subjects:	T Technology > T Technology (General) > T55.4 Industrial engineering.Management engineering. > T59.7 Human engineering in industry. Man-machine systems
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Mechatronics Engineering Kulliyyah of Engineering
Depositing User:	Dr. Md. Raisuddin Khan
Date Deposited:	26 Dec 2024 09:40
Last Modified:	26 Dec 2024 09:40
URI:	http://irep.iium.edu.my/id/eprint/117009

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