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

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 ga...

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Main Authors: Hamed, Hamed, Khan, Md. Raisuddin
Format: Proceeding Paper
Language:English
English
Published: IEEE 2024
Subjects:
T59.7 Human engineering in industry. Man-machine systems
Online Access:http://irep.iium.edu.my/117009/7/117009_AI-based%20detection%20of%20potholes.pdf
http://irep.iium.edu.my/117009/8/117009_AI-based%20detection%20of%20potholes_Scopus.pdf
http://irep.iium.edu.my/117009/
https://ieeexplore.ieee.org/document/10652516
https://doi.org/10.1109/ICOM61675.2024.10652516
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spelling my.iium.irep.1170092024-12-26T01:40:13Z http://irep.iium.edu.my/117009/ AI-based detection of potholes ahead of a visually impaired person using ultrasonic sensors array and camera for blind navigation Hamed, Hamed Khan, Md. Raisuddin T59.7 Human engineering in industry. Man-machine systems 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. IEEE 2024-09-04 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/117009/7/117009_AI-based%20detection%20of%20potholes.pdf application/pdf en http://irep.iium.edu.my/117009/8/117009_AI-based%20detection%20of%20potholes_Scopus.pdf 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. https://ieeexplore.ieee.org/document/10652516 https://doi.org/10.1109/ICOM61675.2024.10652516
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
topic T59.7 Human engineering in industry. Man-machine systems
spellingShingle T59.7 Human engineering in industry. Man-machine systems
Hamed, Hamed
Khan, Md. Raisuddin
AI-based detection of potholes ahead of a visually impaired person using ultrasonic sensors array and camera for blind navigation
description 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.
format Proceeding Paper
author Hamed, Hamed
Khan, Md. Raisuddin
author_facet Hamed, Hamed
Khan, Md. Raisuddin
author_sort Hamed, Hamed
title AI-based detection of potholes ahead of a visually impaired person using ultrasonic sensors array and camera for blind navigation
title_short AI-based detection of potholes ahead of a visually impaired person using ultrasonic sensors array and camera for blind navigation
title_full AI-based detection of potholes ahead of a visually impaired person using ultrasonic sensors array and camera for blind navigation
title_fullStr AI-based detection of potholes ahead of a visually impaired person using ultrasonic sensors array and camera for blind navigation
title_full_unstemmed AI-based detection of potholes ahead of a visually impaired person using ultrasonic sensors array and camera for blind navigation
title_sort ai-based detection of potholes ahead of a visually impaired person using ultrasonic sensors array and camera for blind navigation
publisher IEEE
publishDate 2024
url http://irep.iium.edu.my/117009/7/117009_AI-based%20detection%20of%20potholes.pdf
http://irep.iium.edu.my/117009/8/117009_AI-based%20detection%20of%20potholes_Scopus.pdf
http://irep.iium.edu.my/117009/
https://ieeexplore.ieee.org/document/10652516
https://doi.org/10.1109/ICOM61675.2024.10652516
_version_ 1819909414844366848
score 13.226497

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