Detection of Potholes on Roads using a Drone

Authors

  • HemaMalini B.H BMS Institute of Technology and Management
  • Akshay Padesur BMS Institute of Technology and Management
  • Manoj Kumar V BMS Institute of Technology and Management
  • Atish Shet BMS Institute of Technology and Management

DOI:

https://doi.org/10.4108/eai.19-10-2021.171546

Keywords:

Pothole detection, Drone, Deep Learning, sensing systems, thresholding, YOLOv3, naïve-bayes classifier, K-Means

Abstract

Locating potholes and repairing them is essential, but it has always been a time consuming task for the authorities. This paper presents a way that can help the authorities speed up the pothole detection process by the use of a camera-enabled Unmanned Aerial Vehicle drone. The system is further enabled with a geo-tag and reports the presence of a pothole to the central database which is accessible by the relevant authorities and the common road users. The potholes are located on an open-source map, through which the users using the road can take caution. This increases public safety and helps the concerned authorities take action faster. The model is trained with YOLOv3 algorithm to even detect potholes filled with water, and distinguish potholes from dark road patches, and etc. The results show good accuracy of 85% in detecting the potholes with a low false-negative and false-positive rate.

Downloads

Download data is not yet available.

Downloads

Published

19-10-2021

How to Cite

1.
B.H H, Padesur A, Kumar V M, Shet A. Detection of Potholes on Roads using a Drone. EAI Endorsed Trans Energy Web [Internet]. 2021 Oct. 19 [cited 2024 Apr. 29];9(38):e4. Available from: https://publications.eai.eu/index.php/ew/article/view/77