Pothole detection using YOLOv5 Computer Vision Project
Updated 2 years ago
Metrics
Here are a few use cases for this project:
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Road Maintenance and Repair: Municipalities, state highway agencies, or any road management entities can leverage this model to regularly monitor road conditions. Automated detection of potholes can alert maintenance crews to areas in need of repair, thereby enabling more proactive and efficient road maintenance.
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Automotive Industry: Automobile manufacturers or autonomous vehicle software developers could use the model to advance their car's driving assist features, or to improve safety in self-driving vehicles. Inclusion of pothole detection can help vehicles navigate more safely by avoiding detected potholes.
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Traffic Management: The model could be used in traffic management systems to alert drivers about potholes ahead through traffic message channels or navigation apps, potentially preventing road accidents caused due to the sudden appearance of potholes.
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Insurance Industry: Insurance companies could leverage it to evaluate claims related to pothole-induced vehicle damage. The use of AI in determining the degree of damage could streamline the claims process.
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Infrastructure Planning and Development: City planners or infrastructure developers may use this model to assess the road conditions in specific areas. This could help in allocating resources for infrastructure development, based on the frequency of pothole detection.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
pothole-detection-using-yolov5_dataset,
title = { Pothole detection using YOLOv5 Dataset },
type = { Open Source Dataset },
author = { Projects },
howpublished = { \url{ https://universe.roboflow.com/projects-hjaax/pothole-detection-using-yolov5 } },
url = { https://universe.roboflow.com/projects-hjaax/pothole-detection-using-yolov5 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { mar },
note = { visited on 2024-11-23 },
}