ntroduction: Structural Health Monitoring (SHM) plays a crucial role in ensuring the resilience of buildings and infrastructure in earthquake-prone regions. Traditional SHM methods often face challenges related to sensor placement, data interpretation, and real-time damage detection. Recent advancements in IoT and machine learning offer opportunities to enhance SHM effectiveness, improving early fault detection and predictive maintenance strategies. Methods: This patent develops a novel SHM framework integrating real-time data acquisition, machine learning analytics, and optimized sensor placement. Simulated sensor responses are combined with real-world seismic data to refine damage detection algorithms. The patent is supported by a patented methodology that improves data interpretation, minimizes uncertainties in seismic response evaluation, and adapts SHM systems to various structural configurations. Results: The proposed approach significantly enhances the accuracy of structural assessment, reducing false alarms and improving early damage detection. The integration of IoT technologies facilitates continuous monitoring, while optimized sensor deployment increases data reliability. Experimental validation confirms the effectiveness of the framework in detecting structural vulnerabilities and predicting maintenance needs. Discussion: The integration of intelligent sensing and learning algorithms addresses key limitations of conventional SHM systems. The ability to adapt to varied structural conditions, reduce diagnostic uncertainty, and provide timely alerts marks a significant advancement. Nonetheless, challenges remain in scaling the system for widespread deployment and ensuring reliability under diverse environmental conditions. Conclusion: By leveraging advanced computational techniques and intelligent sensor placement strategies, this research contributes to the development of more cost-effective and adaptable SHM solutions. The findings emphasize the importance of refining monitoring techniques, addressing implementation challenges, and ensuring the long-term reliability of SHM systems in harsh environments. conclusion: This work effectively highlights the role of Structural Health Monitoring (SHM) systems in seismic performance evaluation. It emphasizes that SHM systems help engineers enhance earthquake resilience by providing real-time data on how structures respond to seismic forces. These insights enable more robust building designs and guide retrofitting efforts, which are essential for improving the safety of structures in earthquake-prone areas.
Ghemari et al. (Tue,) studied this question.