Detection of Potholes on Roads using a Drone
DOI:
https://doi.org/10.4108/eai.19-10-2021.171546Keywords:
Pothole detection, Drone, Deep Learning, sensing systems, thresholding, YOLOv3, naïve-bayes classifier, K-MeansAbstract
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.
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