Visual process maps: a visualization tool for discovering habits in smart homes

Abstract

Models of human habits in smart spaces can be expressed by using a multitude of representations whose readability influences the possibility of being validated by human experts. The visual analysis by domain experts allows to identify stages of human habits that could be automatized or simplified by redesigning the environment. In this paper, we present a visual analysis pipeline for graphically visualizing human habits, starting from the sensor log of a smart space,. We apply techniques borrowed from the area of business process automation and mining on a version of the sensor log preprocessed in order to translate raw sensor measurements into human actions. The proposed method is employed to automatically extract models to be reused for ambient intelligence. A user evaluation demonstrates the effectiveness of the approach, and compares it with respect to a relevant state-of-the-art visual tool, namely Situvis.