Introducing USED: Urban Seismic Event Detection

Abstract

In this paper, Urban Seismic Event Detection (USED), a deep learning-based technique, is introduced to extract information about urban seismic events. As large labelled datasets for this research are not publicly available, a scheme is presented to synthesize training data by using a small batch of manually labelled field data. Unlabelled field data can also be leveraged while training using semi-supervised learning, and a mean-teacher approach is discussed. The trained models are tested using synthetic and real data. It is successfully demonstrated that deep learning models can identify urban seismic events when trained solely on synthetic data. The insights and shortcomings of this approach are also discussed while providing potential directions for future research.