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Dr. Krishnareddy K. R. is Professor and Head of the Department of Computer Science and Engineering at SJM University, Karnataka, India. His research interests include Artificial Intelligence, Machine Learning, Structural Health Monitoring, Computer Vision, and Smart Infrastructure Systems.
Structural integrity is an essential component of civil infrastructure, encompassing bridges, buildings, tunnels, dams, highways, and industrial facilities. Timely identification of fissures and structural anomalies is crucial for averting catastrophic failures, minimising maintenance expenditures, and safeguarding public safety. Conventional inspection techniques are frequently arduous, protracted, and prone to human mistake. Artificial Intelligence (AI), especially Machine Learning and Deep Learning methodologies, has emerged as a revolutionary approach for automatic structural fracture identification using image analysis, sensor data processing, and astute decision-making. Integrating AI with computer vision, drones, IoT sensors, and cloud-based monitoring systems enhances the accuracy and efficiency of structural health assessments. This chapter examines the ideas, methodology, designs, applications, problems, and future developments of AI-driven structural crack detection systems, emphasising their importance in smart infrastructure and predictive maintenance.