Monitoring Techniques for Structural Health of Roads Using Emerging Technologies: A Systematic Re-View of the Last Five Years

Abstract

This systematic review examines the most recent techniques used to monitor the structural health of roadways, with a special focus on emerging technologies applied over the past five years. The progressive deterioration of road networks and the limitations of traditional inspection methods have driven the development of more precise, automated, and efficient solutions. The technologies analyzed include LiDAR laser scanning, drones equipped with computer vision, visual sensors, mobile cameras, ground-penetrating radar (GPR), and unmanned aerial vehicles (UAVs). Each technique was assessed based on its accuracy and the type of pavement distress it can identify, such as cracks, potholes, and surface deformations. The findings indicate that these tools enhance the efficiency and safety of inspections, enabling real-time data collection. Additionally, there is a growing trend toward the integration of artificial intelligence algorithms to automate data analysis. However, data heterogeneity and the need for cross-domain model adaptation may affect performance and scalability in large-scale or multi-source scenarios. Overall, this study provides an updated perspective on the application of emerging technologies in road infrastructure management, contributing to the development of innovative strategies for sustainable and intelligent roadway maintenance.OPEN ACCESS Received: 09/09/2025 Accepted: 09/12/2025 The search strategy was designed based on the PICOC framework, using the following Figure 1: Most frequent and trending

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