Intelligent Road Maintenance

Abstract

Smart city sustainability is supported by developing efficient, well-maintained transportation infrastructure, particularly road networks, which impacts the safety and well-being of all users, including civilians and critical government service providers such as police and healthcare professionals. Roads naturally degrade over time owing to causes such as poor weather, natural disasters, and large traffic volumes, resulting in worsening conditions that pose safety hazards and operating issues. Smart cities are progressively implementing predictive maintenance inside Intelligent Transportation Systems (ITS) frameworks to improve service quality and prolong road durability. With the use of deep learning (DL) models like (CNN), (ANN), (RNN), and (DNN), predictive maintenance makes it possible to identify road issues early and predict maintenance requirements based on variables like traffic volume and environmental conditions. This proactive strategy lowers maintenance costs and extends the infrastructure's lifetime while improving road safety and the overall travel experience.