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: | , |
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| Format: | Proceeding Paper |
| Language: | English English |
| Published: |
IEEE
2024
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| Subjects: | |
| 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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| Summary: | 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. |
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