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

  • Francesco Leotta
  • Massimo MecellaEmail author
  • Daniele Sora
Original Research
  • 20 Downloads

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.

Keywords

Visual process maps Habit mining Habit visualization 

Notes

Acknowledgements

Results in this paper have been obtained with an academic license of Disco freely provided by Fluxicon. The work of Daniele Sora has been partly supported by the Lazio regional project SAPERI & Co (FILAS-RU-2014-1113), the work of Francesco Leotta has been partly supported by the Lazio regional project Sapientia (FILAS-RU-2014-1186), all the authors have been also partly supported by Italian project Social Museum e Smart Tourism (CTN01-00034-23154), Italian project NEPTIS (PON03PE-00214-3) and Italian project RoMA–Resilence of Metropolitan Areas (SCN-00064).

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Dipartimento di Ingegneria Informatica, Automatica e Gestionale Antonio RubertiSapienza Università di RomaRomeItaly

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