The proposed system demonstrates improved pothole detection accuracy in real-time environments, indicating effective road safety management.
Potholes pose a significant risk to road safety and contribute to increased maintenance costs. This paper presents the development of a compact, real-time pothole detection and localization system that leverages low-cost, embedded technologies. The proposed system employs a Raspberry Pi as the primary processing unit, interfaced with an Arducam depth camera for surface profiling, a Neo-6M GPS module for geo-tagging, and an Inertial Measurement Unit (IMU) for motion stabilization and noise reduction. Together, these components enable accurate detection of potholes in dynamic environments while minimizing false positives caused by minor surface irregularities. Field testing demonstrated the system's ability to achieve an average geo-location accuracy of ±2 meters, along with reliable differentiation between potholes and less severe road surface defects. To enhance user engagement and maintenance planning, a mobile application is proposed as a future enhancement. The app would offer real-time hazard alerts and map-based visualization for both drivers and road maintenance authorities. The integrated system offers a scalable, cost-effective solution for automated road condition monitoring and infrastructure management.
No takes yet. Share an insight, caveat, or question.
Bhoyar et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: