Towards A Self-Learning Library For Vibration Data

Vibration data from building can reflect human activities such as human movement. Lack of relative labeled dataset has been a major challenge for conducting such analysis job. We aim to explore possibilities to produce footstep metadata automatically through machine learning techniques. In this paper, we perform an analysis on identifying human footsteps by utilizing deep neural network as a classifier.