The modern structural health monitoring (SHM) paradigm of transforming in situ, real-time data acquisition into actionable decisions regarding structural performance, health state, maintenance, or life cycle assessment has been accelerated by the rapid growth of “big data” availability and advanced data science. Such data availability coupled with a wide variety of machine learning and data analytics techniques have led to rapid advancement of how SHM is executed, enabling increased transformation from research to practice. This book intends to present a representative collection of such data science advancements used for SHM applications, providing an important contribution for civil engineers, researchers, and practitioners around the world.

This book should be of interest to students and practitioners of materials science, production engineering and engineering design.

This AI system can be applied in various real-world scenarios, such as: - Bridge Monitoring: Continuous monitoring of bridges to detect early signs of wear and prevent collapses. - Building Inspections: Routine assessments of high-rise buildings to identify structural weaknesses. In the future, this AI could be explored and used by the entire population to identify construction anomalies and structural pathologies. Suppose you are in your room and suddenly notice a large crack in the main pillar of your roof. When this AI is ready, you will simply need to take 2 or 3 photos of the concerned area from different angles. The device will immediately analyze the damage, compare it with its data, describe the situation, and provide you with recommendations. The system could also automatically alert engineers and the government based on the severity of the case. Additionally, the system will have an integrated thermal camera to analyze thermal factors, determining the depth of the damage and the affected area.

A critical review of key developments and latest advances in Structural Health Monitoring technologies applied to civil engineering structures, covering all aspects required for practical application Structural Health Monitoring (SHM) provides the facilities for in-service monitoring of structural performance and damage assessment, and is a key element of condition based maintenance and damage prognosis. This comprehensive book brings readers up to date on the most important changes and advancements in the structural health monitoring technologies applied to civil engineering structures. It covers all aspects required for such monitoring in the field, including sensors and networks, data acquisition and processing, damage detection techniques and damage prognostics techniques. The book also includes a number of case studies showing how the techniques can be applied in the development of sustainable and resilient civil infrastructure systems. Structural Health Monitoring of Large Civil Engineering Structures offers in-depth chapter coverage of: Sensors and Sensing Technology for Structural Monitoring; Data Acquisition, Transmission, and Management; Structural Damage Identification Techniques; Modal Analysis of Civil Engineering Structures; Finite Element Model Updating; Vibration Based Damage Identification Methods; Model Based Damage Assessment Methods; Monitoring Based Reliability Analysis and Damage Prognosis; and Applications of SHM Strategies to Large Civil Structures. Presents state-of-the-art SHM technologies allowing asset managers to evaluate structural performance and make rational decisions Covers all aspects required for the practical application of SHM Includes case studies that show how the techniques can be applied in practice Structural Health Monitoring of Large Civil Engineering Structures is an ideal book for practicing civil engineers, academics and postgraduate students studying civil and structural engineering.

Important new information on sensors, monitoring, prognosis, networking, and planning for safety and maintenance.