Pothole Detection using Computer Vision and Raspberry Pi

Authors

  • Syed Umaid Ahmed FAST National University of Computer and Emerging Sciences Karachi, Pakistan.
  • Hamza Ayaz Department of Electrical Engineering Deggendorf Institute of Technology Deggendorf, Germany.
  • Syed Abdul Sami Rizvi Department of Electrical Engineering National University of Sciences and Technology Karachi, Pakistan.
  • Muhammad Harris Hashmi Department of Computer Science University of Alabama at Birmingham Birmingham, USA.
  • Mujtaba Humayon Department of Computer Science University of Alabama at Birmingham Birmingham, USA .
  • Muhammad Salik Salam Department of Computer Science University of Alabama at Birmingham Birmingham, USA.

Keywords:

Pothole, Raspberry-Pi, Computer Vision, Image Processing, Night vision camera, Machine Learning, Disturbance Sensor, TensorFlow

Abstract

One of the main reasons for the number of potholes rising overtime is the poor road-maintenance system along with aging roads with no maintenance. This then jeopardizes road safety as well as transport efficiency, resulting in being the lead cause of car accidents. To address the problems associated with potholes the size and location should be determined. Efficient road-maintenance strategies require a pothole database, incorporating a specific pothole detection system that can collect information at low cost and cover a wide area. However, pothole detection encompasses prolong manual steps of detection. Recently made, pothole detection systems using vibration or laser scanning are not only unstable but result in accurate detection as well as are expensive respectively. Thus, in this paper, we introduce a newly efficient way for pothole detection A Night Vision camera not only detects potholes over a wide area at low cost but also owns a novel pothole detection algorithm that has been specifically designed to work with the embedded computing environment of the camera. Our system shows experimental results which prove that our system successfully detects potholes in real-time.

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Published

2024-06-01

How to Cite

Syed Umaid Ahmed, Hamza Ayaz, Syed Abdul Sami Rizvi, Muhammad Harris Hashmi, Mujtaba Humayon, & Muhammad Salik Salam. (2024). Pothole Detection using Computer Vision and Raspberry Pi. Journal of Computing & Biomedical Informatics, 7(01), 690–695. Retrieved from https://jcbi.org/index.php/Main/article/view/515