Persim 3D: Context-Driven Simulation and Modeling of Human Activities in Smart Spaces

Abstract

Automated understanding and recognition of human activities and behaviors in a smart space (e.g., smart house) is of paramount importance to many critical human-centered applications. Recognized activities are the input to the pervasive computer (the smart space) which intelligently interacts with the users to maintain the application's goal be it assistance, safety, child-development, entertainment or other goals. Research in this area is fascinating but severely lacks adequate validation which often relies on datasets that contain sensory data representing the activities. Availing adequate datasets that can be used in a large variety of spaces, for different user groups, and aiming at different goals is very challenging. This is due to the prohibitive cost and the human capital needed to instrument physical spaces and to recruit human subjects to perform the activities and generate data. Simulation of human activities in smart spaces has therefore emerged as an alternative approach to bridge this deficit. Traditional event-driven approaches have been proposed. However, the complexity of human activity simulation was proved to be challenging to these initial simulation efforts. In this paper, we present Persim 3D-an alternative context-driven approach to simulating human activities capable of supporting complex activity scenarios. We present the context-activity-action nexus and show how our approach combines modeling and visualization of actions with context and activity simulation. We present the Persim 3D architecture and algorithms, and describe a detailed validation study of our approach to verify the accuracy and realism of the simulation output (datasets and visualizations) and the scalability of the human effort in using Persim 3D to simulate complex scenarios. We show positive and promising results that validate our approach.