Rapid Assessment and Damage Detection of Bridge Health Conditions Through Advanced Sensing Integrated with Artificial Intelligence

With the rapid economic development, the number of constructed bridges has surged globally. These structures inevitably experience progressive degradation in structural performance during their service life, necessitating periodic health assessment. However, given the vast scale of modern bridge transportation networks, conventional inspection methods—whether manual patrols or structural health monitoring systems—are often time-consuming, inefficient, and prohibitively expensive.In recent years, mobile sensing-based bridge inspection technologies have emerged as a promising solution for rapid and accurate health evaluation of extensive bridge networks. These technologies primarily leverage intelligent sensing capabilities to achieve holistic structural condition perception, providing critical data support for bridge evaluation. Key enabling technologies include intelligent mobile sensing devices, fiber-optic sensors, and digital image correlation techniques.This special issue addresses the industry pain points of low efficiency and high costs associated with traditional bridge inspection methods. By integrating mobile sensing technologies (e.g., vehicle/drone-mounted sensors), artificial intelligence algorithms (e.g., deep learning-based damage recognition), intelligent sensing systems (e.g., fiber optic/visual sensor arrays), and digital image analysis techniques, it aims to establish a rapid health assessment framework for large-scale bridge networks. Research scope encompasses the development of sensing technologies (e.g., high-precision mobile measurement devices), optimization of data-driven damage detection algorithms, multi-source data fusion methods for structural state evaluation, and technical validation/standardization studies in practical engineering applications. Through interdisciplinary innovation, this initiative promotes the transformation of bridge health monitoring from manual empirical judgment to intelligent, automated, and precision-oriented paradigms, providing theoretical support and technological frameworks for smart infrastructure maintenance and management.Topics of interest include (but are not limited to):Innovations and Applications of Mobile Sensing Technologies;AI-Driven Damage Detection Algorithms;Multi-Source Data Fusion and Condition Assessment;Engineering Case Validation and Technical Standardization;Interdisciplinary Technology Integration Exploration;Disaster Response and Emergency Assessment Technologies;Frontier Challenges and Future Directions; Topic editors: Zhi Li, Liang Xu, Zhi-Lu Wang, Yanjie Zhu Source: https://www.frontiersin.org/research-topics/76493/rapid-assessment-and-damage-detection-of-bridge-health-conditions-through-advanced-sensing-integrated-with-artificial-intelligence