Skip to Main Content
Earthquake engineering applications is an emerging area for sensor networks where survivability is a major concern. Due to the nature of the application, it is not possible to depend on a continuously connected network. It is vital to sustain the functionality during the disconnected times that might occur following seismic activity. In addition, due to resource constraints such as data storage capacity as well as the power supply, it is important to reduce the amount of communication and data storage requirements. Data aggregation is a technique to reduce the amount of data to this end. To date, however, data aggregation for accelerogram readings has either been computationally intensive, representing a barrier to its acceptance in sensor networks, or resulted in critical data loss and inaccurate interpretations. In this article we study the application-based requirements of accelerogram-based sensor networks. We then propose a data aggregation method to enable orders of magnitude improvement in storage and transmission of the observations of a seismic activity without losing critical information. We present results from our performance analysis based on a wide variety of real earthquake data. Our results suggest orders of magnitude improvement in storage and communications with our approach.