ISI Journals

Maintaining the infrastructure of roads is critical for ensuring the safety and efficiency of transportation systems. However, the traditional methods of road maintenance are often inefficient, reactive, and costly. In recent years, researchers have explored the use of machine learning techniques to improve road maintenance by incorporating various data sources, including pavement condition, social network data, and environmental factors. In this article, we present a comprehensive analysis of the impact of social network data, pavement condition, and environmental factors on road maintenance using machine learning algorithms. We also discuss the implications of our findings for the future of road maintenance.