AI-driven seismic durability of concrete structures using reinforcement learning

In order to improve the oversight, security, and upkeep of smart city infrastructures, this article investigates the potential for combining IoT with structural health monitoring (SHM) systems and cutting-edge ML methods. The suggested solution overcomes the shortcomings of conventional monitoring methods by enhancing the real-time gathering and analysis of data on structural integrity through the use of sensors powered by the Internet of Things (IoT) and deep learning (DL) algorithms. The approach achieves over 90% accuracy in forecasting structural health post-seismic events, demonstrating high prediction accuracy with up to 93,500 data points analysed for seismic response models of reinforced concrete (RC) structures. Moreover, cloud computing allows for effective data storage and remote access, guaranteeing that steps are taken promptly to ensure the safety of urban infrastructure. These advancements lay the groundwork for smart city solutions that are scalable, efficient, and dependable; they improve sustainability and resilience by using cutting-edge SHM and IoT technology.