## 6 Conclusions  
In this study, an empirical study based on previous research into a cochlea-inspired artificial filter (CAFB) bank for SHM was performed. To do that, a data compression technology-based intelligent data acquisition (IDAQ) system was developed based on digital software design by embedding the previously developed CAFB into the wireless sensing system. The following conclusions were obtained by applying the developed CAFB-based IDAQ system to a model bridge and performing modal testing. 1. The band-pass filter optimizing algorithm of the developed CAFB was effective in acquiring just the frequency signal containing the significant modes of interest) out of the wide frequency contents of random signals. In particular, the artificial filter bank optimized by using the representative random waveform (based on the El-Centro earthquake) can be utilized as a technology to acquire the dynamic response of large civil structures with a frequency range below 10 Hz. 2. The peak-picking algorithm of the developed CAFB is effective in compressing the data size by selectively re-sampling only the peak values containing the valid modal information out of the random dynamic responses. This data compression technology can be efficiently used as a \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Bending** & **Wireless (Hz)** & **Reconstruction (Hz)** & **Error Ratio (\%)** & **Compressive (Hz)** & **Error Ratio (\%)** \\ \hline
1 st & 2.736 & 2.736 & 0.000 & 2.735 & 0.036 \\
2 nd & 4.104 & 4.104 & 0.000 & 4.005 & 2.412 \\
3 rd & 6.058 & 6.058 & 0.000 & 6.057 & 0.016 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Comparison of the natural frequency (reconstruction and compressive. vs. wireless raw signal). Figure 14: Comparison of time and frequency domain of peak-picking (compression) signal using the IDAQ system: (**a**) time domain (original, reconstruction, and peak-picking signal); and (**b**) frequency domain (original, reconstruction, and peak-picking signal). \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**RE** & **Reconstruction Efficacy (\%)** & **CR** & **Compressive Efficacy (\%)** \\ \hline
0.4461 & 55.39 & 0.095 & 90.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Performance of CAFB (reconstruction and compressing effectiveness). technology to operate and manage the measurement DB and also to overcome the limitations of wireless RF communications, which has emerged in WSN-based SHM technology. 3. The CAFB can be optimized flexibly with a random standard signal, and it can be utilized as a technology to acquire the dynamic response not only from civil structures, but also from other structures (e.g., machines used in industry). Furthermore, it was observed that the reconstruction signal and compressive signal evaluated in this study are not only capable of reconstructing in the time domain but also reflect the modal information of the frequency domain. 4. In this paper, CAFB was optimized on the basis of three target modes in order to efficiently acquire dynamic responses concerned on the model structure, and its performance was quantitatively evaluated through modal experiments. If the target structure is not a civil structure, but a machine, a plant, or other facilities whose frequency of dynamic responses is different from the one concerned in this paper, it can be newly optimized for a new purpose. The CAFB, which was evaluated in this paper can, thus, be variably applied with flexible readjustment and optimization in regard to the range of frequency and responses of a target structure. 5. Ultimately, since the CAFB-based IDAQ system developed in this study can acquire the compressed size of the valid dynamic response around the frequency range of interest it is, therefore, relevant with respect to the economy and efficiency when measuring the dynamic response of civil structures in real-time and it is determined that this system can provide a new paradigm for structural health monitoring using WSNs. 6.