## 6 Conclusions  
Structural health monitoring has become a crucial tool for evaluating the safety and performance of critical infrastructure, enabling the early detection of potential damage and supporting maintenance planning. The use of advanced methodologies to analyze dynamic responses under various excitation sources has enhanced the understanding of structural behavior and resilience under environmental conditions and external events. The results of this study on structural health monitoring (SHM) conducted on a reinforced concrete building in Valparaiso, Chile, can be extended and generalized to other similar cases through several key aspects. The methodology employed, based on the SSI-COV method, provides a robust framework for analyzing structural frequencies, assessing their stability over time, and detecting changes in structural behavior under various excitation sources, such as ambient vibrations, seismic events, and construction-induced vibrations. This approach is adaptable to other infrastructures, including critical facilities like bridges, tunnels, and historical buildings, where early damage detection is vital for safety. Complementing experimental data with numerical models, as demonstrated in this study, enhances the reliability of findings by providing additional insights into modal frequencies and validating the results. Advanced statistical methods, such as probabilistic or Bayesian approaches, could further refine the characterization of dynamic behavior by quantifying uncertainties and enabling the calibration of finite element (FE) models  
Figure 19: Temporal evolution of the frequencies for system order 24.  
through optimization processes [38; 39]. The strategic placement of synchronized sensors ensured sufficient spatial coverage and accurate frequency identification, despite the limited number of sensors. This principle can be generalized to other structures by employing low-cost sensors, enabling real-time monitoring even in regions with limited resources. The study highlights the distinct effects of various excitation sources, emphasizing the importance of monitoring diverse types of vibrations to capture a complete dynamic profile of the structure. Moreover, the consistent identification of the 2.4 Hz frequency across all excitation sources underscores its relevance as a baseline indicator of structural health, which could be tracked in similar structures to detect deviations over time. Integrating SHM data into digital models or digital twins could further enhance real-time monitoring, simulate structural responses under varying conditions, and optimize maintenance strategies, providing a scalable and cost-effective solution for diverse infrastructures. Future improvements could include the integration of advanced statistical methods to improve the interpretation of results, particularly under variable conditions or with limited data, highlighting the potential of combining deterministic and probabilistic approaches for structural monitoring. Finally, expanding SHM systems into regional seismic monitoring networks would enable large-scale assessments of structural stability, providing valuable insights for regional planning and resilience strategies. Conceptualization, S.L.-A., A.L., J.A.L.-G. and S.F. ; methodology, S.L.-A., A.L., S.F. and J.A.L.-G.; software, S.L.-A. and M.G. ; formal analysis, S.L.-A. ; investigation, S.F., A.L., E.A. and J.A.L.-G.; resources, S.F., J.A.L.-G., A.L. and E.A. ; data curation, S.L.-A., A.L. and S.F. ; writing--original draft preparation, S.L.-A. ; writing--review and editing, S.F., A.L., E.A., M.G. and J.A.L.-G.; supervision, S.F., A.L. and M.G. All authors have read and agreed to the published version of the manuscript. This research was funded by Ministerio de Economia y Competitividad grant number PID2021-126405 OB-C32. Part of this research has also been funded by the Chilean Fondo Nacional de Ciencia y Tecnologia, Fondecyt Iniciacion en Investigacion through Grant #11241507.