
Comprehensive Road Defect Indexing System using Hybrid Machine Learning Approach for Automated Defect Detection, Classification, and Predictive Analysis
The rationale for this project lies in the pressing need for intelligent, automated road monitoring systems that can cater to diverse urban environments. By leveraging AI, this project aims to bridge the gap between manual inspections and the demand for efficient infrastructure management. It aligns with global efforts to implement smart city initiatives, improve transportation systems, and enhance road safety through technological innovation. This approach is also critical for addressing the increasing complexity of road networks and the challenges posed by climate change, population growth, and economic expansion.
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