Paper Title
AI-Based Pothole Detection
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Registration ID: IJNRD_307523
Published ID: IJNRD2506078
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Keywords
Random forest (RF), support vector machine (SVM), asphalt roads, pavement distress, multispectral imaging, artificial neural network (ANN), and unmanned aerial vehicle (UAV).
Abstract
Since asphalt roads are the foundation of every land transportation system, their quality will deteriorate as they are used due to the aging and surface deterioration.Ultimately, certain road pavement distresses might emerge on the surface of the road, like the most typical cracks and potholes. Nowadays, several new types of remote sensing data—such as digital pictures, light detection and ranging, and radar—that don't damage the pavement are frequently employed to identify pavement distresses in use of multispectral imagery, which displays both the spatial and spectral characteristics of objects. In order to differentiate between normal pavement and pavement damage, our study used multispectral pavement photos taken by unmanned aerial vehicles (UAVs). (such as potholes and cracks) using machine learning techniques including random forest, artificial neural networks, and support vector machines. This study compares the performance of various data types and models and shows that a UAV remote sensing system provides a new tool for tracking the condition of asphalt roads, which can be used to support decisions about road maintenance procedures
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How To Cite (APA)
Devesh S Narkhede, Shivaji R Vasekar, Jasbir S Sharma, Vishvak R Choubisa, & Om S Patil (June-2025). AI-Based Pothole Detection. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 10(6), a705-a711. https://ijnrd.org/papers/IJNRD2506078.pdf
Issue
Volume 10 Issue 6, June-2025
Pages : a705-a711
Other Publication Details
Paper Reg. ID: IJNRD_307523
Published Paper Id: IJNRD2506078
Research Area: Science and Technology
Author Type: Indian Author
Country: Pimpri Chinchwad, MAHARASHTRA, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2506078.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2506078
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