Demonstrates AI-based fault detection in road surfaces, implying enhanced safety and reduced costs.
Road surface damage such as potholes, cracks, and uneven patches poses serious risks to vehicles and public safety. This project presents an IoT-based road surface analysis system that uses MEMS data and artificial intelligence for automatic fault detection. The system continuously collects vibration and motion data while tracking real-time location information. Advanced machine learning algorithms analyze the data to accurately identify and classify road defects The processed information is transmitted to a cloud platform and accessed through a mobile application for monitoring and decision-making. This approach reduces manual inspection efforts, lowers maintenance costs, and improves response time.
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S et al. (2026) studied this question.
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