Abstract
Among the most important decisions to be taken in modeling human habits in smart spaces there is the choice of the technique to be adopted: models can be expressed by using a multitude of formalisms, all with differently proven effectiveness. However, a crucial aspect, often underestimated in its importance, is the readability of the model: it influences the possibility of validating the model itself by human experts. Possible solutions for the readability issue are offered by Business Process Modeling techniques, designed for process analysis: to apply process automation and mining techniques on a version of the sensor log preprocessed in order to translate raw sensor measurements into human actions. The paper also presents some hints of how the proposed method can be employed to automatically extract models to be reused for ambient intelligence, analysing the challenges in this research field.
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 the Italian projects NEPTIS, SM&ST and RoMA.
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Sora, D., Leotta, F., Mecella, M. (2018). An Habit Is a Process: A BPM-Based Approach for Smart Spaces. In: Teniente, E., Weidlich, M. (eds) Business Process Management Workshops. BPM 2017. Lecture Notes in Business Information Processing, vol 308. Springer, Cham. https://doi.org/10.1007/978-3-319-74030-0_22
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DOI: https://doi.org/10.1007/978-3-319-74030-0_22
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