This study investigated operational and structural health monitoring (SHM) as well as damage evaluations for building structures. The study involved damage detection and the assessment of buildings by placing sensors and by assuming weak areas, and considered situations of assessment and self-monitoring. From this perspective, advanced sensor technology and data acquisition techniques can systematically monitor a building in real time. Furthermore, the structure’s response and behavior were observed and recorded to predict the damage to the building. In this paper, we discuss the real-time monitoring and response of buildings, which includes both static and dynamic analyses along with numerical simulation studies such as finite element analysis (FEA), and recommendations for the future research and development of SHM are made.

Structural health monitoring (SHM) has evolved into an indispensable component for ensuring the safety, durability, and life-cycle efficiency of civil infrastructure. Over the past five years, significant technological advancements have been made in innovative sensing systems, facilitating real-time assessment of structural performance and the early detection of deterioration. This comprehensive review presents recent developments in smart sensor-based SHM, with particular emphasis on the convergence of the Internet of Things (IoT), artificial intelligence (AI), and digital twin (DT) frameworks. Our review critically examines advances in fiber-optic, piezoelectric, MEMS-based, vision-based, acoustic, and environmental sensors, as well as emerging multi-sensor fusion architectures. In addition, bibliometric insights highlight the significant rise in global research activity and influential thematic clusters in SHM between 2020 and 2025. The discussion underscores how AI-integrated data analytics, IoT-enabled wireless networks, and DT-driven virtual replicas enable intelligent, autonomous, and predictive monitoring of bridges, buildings, tunnels, and other large-scale civil infrastructure. Field deployments and case studies are analyzed to bridge the gap between laboratory-scale demonstrations and real-world implementation. Finally, key scientific and practical challenges—including the durability of embedded sensors, the interoperability of heterogeneous data, cybersecurity in connected systems, and the explainability of AI models—are outlined to guide future research. Overall, this review positions contemporary SHM as a transition from traditional damage detection to comprehensive life-cycle management of infrastructure through self-diagnosing, data-centric, and sustainability-driven monitoring ecosystems.

This study investigates the side-impact crashworthiness of a low-floor electric bus with traction batteries integrated into the inter-window pillars of the body structure. A finite-element model of the bus body was developed in Ansys and used to evaluate six impact scenarios involving conventional diesel and battery-integrated configurations. The analysis included evaluation of von Mises stresses, structural safety margins, deformation fields, strain energy, and transient nodal velocity response. The battery-integrated configuration demonstrated improvements in key crashworthiness indicators across the investigated impact scenarios, with both the average maximum deformation and the averaged equivalent stress reduced by approximately one quarter compared with the conventional configuration. The stress state of the inter-window pillars remained below the local structural failure levels observed in the conventional configuration, with the maximum pillar stress criterion reduced by more than half. Simultaneously, lower transient nodal velocities indicated reduced transmission of impact momentum toward the occupant compartment and more efficient redistribution of impact energy through the body structure. The results demonstrate the feasibility of using battery-integrated inter-window pillars as multifunctional structural members that simultaneously serve as energy storage and enhance the side-impact crashworthiness of low-floor electric buses.