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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Kakakde, Kiran S.
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Computer Science & IT Engineering

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Pothole detection model for road safety using computer vision and machine learning Bidve, Vijaykumar S.; Kakakde, Kiran S.; Bhole, Rahul H.; Sarasu, Pakiriswamy; Shaikh, Ashfaq; Mehta, Pradnya Samit; Borde, Santosh P.; Kediya, Shailesh O.
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i4.pp4480-4487

Abstract

Potholes pose significant threats to vehicular movement, causing damage to vehicles and risking the safety of drivers and pedestrians. The escalating issue of potholes has led to substantial financial losses for vehicle owners and drivers. Traditional methods of pothole detection are impractical, necessitating an innovative approach. The study focuses on implementing a detection system capable of accurately identifying potholes, empowering vehicles to adapt their speed or halt to prevent damage. The transformative solution presented in this research leverages cutting-edge technologies, specifically computer vision and machine learning, aiming to enhance road safety and streamline maintenance efforts. By addressing the interdependence of modern civilization on road networks, the Pothole Detection Model promises improved road safety, efficient maintenance practices, and the emergence of an era in intelligent transportation systems. The integration of technology into transportation infrastructure highlights the proactive measures needed to combat road imperfections, ensuring a safer and more efficient road network for the benefit of society.
Co-Authors Bhole, Rahul H. Bidve, Vijaykumar S. Borde, Santosh P. Kediya, Shailesh O. Mehta, Pradnya Samit Sarasu, Pakiriswamy Shaikh, Ashfaq