An implementation of light-weight compression algorithm for wireless sensor network technology in structure health monitoring

Internet-of-Thing (IoT) has been identified as one of the next generation technologies from different aspects. Among different technologies for IoT, wireless-sensor-network (WSN) is one of key technologies to be developed. To demonstrate WSN capabilities in applications, this work developed self-developed sensor node (Super-Node) and applied the device into an on-field structure-health-monitoring (SHM) task. The developed WSN system achieved requirements of SHM applications, i.e. 128 Hz sampling rate with tri-axial acceleration data within one sensor node. By acquired data, the developed system can make the prediction of structure status. In addition, a local-data-processing node and algorithm was also implemented to promote usability of WSN system in SHM applications. With Huffman code implemented, the wireless transmission payload was reduced by 60% and the node capacity can be increased by 3 times. This work not only demonstrated the capability of WSN technologies in on-field SHM applications but also provided a better solution for IoT development.