## 5 Future Works and Perspectives  
The integration of structural health monitoring (SHM) into real-time hybrid simulations (RTHS) of human-structure interaction (HSI) presents a promising avenue for future research. Although current SHM technologies allow for continuous monitoring of footbridges, several aspects remain underdeveloped. Specifically, the future development of SHM in RTHS should focus on improving sensor accuracy, expanding sensing coverage, and developing real-time feedback loops that can more effectively capture the dynamic effects induced by pedestrian loads. These improvements would enhance the fidelity of RTHS in capturing the complex, nonlinear behavior of footbridges under varying HSI scenarios [89; 90].  
Moreover, an essential aspect that future research must address is the recovery of missing measurement data, a common issue in SHM systems. While various methods, such as statistical techniques and machine learning algorithms, have been developed to mitigate the impact of data loss, further advancements are necessary. Future research should explore the application of deep learning models and advanced Kalman filtering methods tailored to the unique demands of RTHS applications. These approaches could offer higher precision  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Test** & **NRMS\({}_{error}\) [\%]** & **FEI** & \(f_{eq}\) [Hz] & \(A_{0}\) & \(e_{DM}\) [\%] & \(e_{MD}\) [\%] & \(\delta\) [ms] \\ \hline \multicolumn{8}{c}{Vertical Transfer System} \\ \hline
1.20 m\(\cdot\)s\({}^{-1}\) & 2.910 & 0.985–0.012i & 2.065 & 0.985 & 0.540 & 2.930 & 2.010 \\  & \(\pm\)0.80 & \(\pm\)0.01 & \(\pm\)0.03 & \(\pm\)0.01 & \(\pm\)0.30 & \(\pm\)0.30 & \(\pm\)0.10 \\ \hline
1.50 m\(\cdot\)s\({}^{-1}\) & 2.900 & 0.987–0.013i & 2.063 & 0.987 & 0.560 & 2.940 & 2.045 \\  & \(\pm\)0.11 & \(\pm\)0.01 & \(\pm\)0.04 & \(\pm\)0.01 & \(\pm\)0.20 & \(\pm\)0.30 & \(\pm\)0.10 \\ \hline
1.80 m\(\cdot\)s\({}^{-1}\) & 2.850 & 0.989–0.012i & 2.065 & 0.989 & 0.560 & 2.880 & 2.085 \\  & \(\pm\)0.16 & \(\pm\)0.01 & \(\pm\)0.03 & \(\pm\)0.01 & \(\pm\)0.30 & \(\pm\)0.30 & \(\pm\)0.10 \\ \hline \multicolumn{8}{c}{Lateral Transfer System} \\ \hline
1.20 m\(\cdot\)s\({}^{-1}\) & 1.450 & 1.005–0.019i & 1.034 & 1.005 & 0.310 & 1.860 & 1.700 \\  & \(\pm\)0.43 & \(\pm\)0.01 & \(\pm\)0.01 & \(\pm\)0.01 & \(\pm\)0.28 & \(\pm\)0.40 & \(\pm\)0.30 \\ \hline
1.50 m\(\cdot\)s\({}^{-1}\) & 1.380 & 1.004–0.011i & 1.045 & 1.004 & 0.310 & 1.770 & 1.600 \\  & \(\pm\)0.36 & \(\pm\)0.01 & \(\pm\)0.01 & \(\pm\)0.01 & \(\pm\)0.29 & \(\pm\)0.37 & \(\pm\)0.20, \\ \hline
1.80 m\(\cdot\)s\({}^{-1}\) & 1.350 & 1.002–0.011i & 1.059 & 1.002 & 0.240 & 1.670 & 1.600 \\  & \(\pm\)0.19 & \(\pm\)0.01 & \(\pm\)0.02 & \(\pm\)0.01 & \(\pm\)0.15 & \(\pm\)0.18 & \(\pm\)0.20 \\ \hline \hline \end{tabular}
\end{table}
Table 3: RTHS evaluation indexes: vertical and lateral transfer systems.  
in data recovery and ensure that missing data do not compromise the accuracy of the simulation results [91; 92].  
Additionally, the long-term objective of integrating SHM and data recovery methods into HSI studies should be the development of autonomous systems capable of real-time damage detection and self-healing mechanisms for data recovery. This would allow for real-time decision-making during RTHS, enabling proactive interventions to mitigate excessive vibrations or structural damage. The continuous improvement of SHM and data recovery technologies will be instrumental in ensuring the resilience, safety, and sustainability of footbridge structures as urban environments continue to evolve.