Wireless sensor networks based-structural health monitoring is being widely researched. To make a better structural health monitoring, real-time acquisition of structural responses is indispensable. However, the data, which is large in number especially when they are of moving structures, are difficult to be measured, and the adaptation of wireless sensor networks further limits structural health monitoring within the capacity of radio frequency. In this study, cochlea-inspired artificial filter bank was developed as a technological way to efficiently acquire dynamic responses at a wireless sensor networks based-structural health monitoring. The cochlea-inspired artificial filter bank developed in this article was enabled to acquire valid dynamic responses of compressed size around the frequency range of interest by simulating raw data to the full regarding to time and frequency of dynamic responses. In addition, the digitalized cochlea-inspired artificial filter bank was also found to fix the disadvantages of analogue filters by its easy and efficient development of logics, optimization, design of software, and real-time autonomous execution. Finally, the cochleainspired artificial filter bank makes it possible to compress and reduce the vast amount of real-time dynamic responses usually obtained by means of a uniform rate of sample, into a manageable size. It is thus expected to open up a new paradigm in the Wireless sensor networks based-structural health monitoring of civil structures by facilitating an efficient measurement and management of data base.