Enabling Process Mining on Sensor Data from Smart Products

M.L. Van Eck, N. Sidorova, W.M.P. Van Der Aalst

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

44 Citaten (Scopus)
754 Downloads (Pure)

Samenvatting

In this paper we address the challenge of applying process mining to discover models of human behaviour from sensor data. This challenge is caused by a gap between sensor data and the event logs that are used as input for process mining techniques, so we provide a transformation approach to bridge this gap. As a result, besides the automatic discovery of process models, the transformed sensor data can also be used by various other process mining techniques, e.g. to identify differences between observed behaviour and expected behaviour. We discuss the transformation approach in the context of the design process of smart products and related services, using a case study performed at Philips where a smart baby bottle has been developed. This case study also demonstrates that the use of process mining can add value to the smart product design process.

Originele taal-2Engels
TitelIEEE RCIS 2016 - IEEE 10th International Conference on Research Challenges in Information Science, 1-3 may 2016, Grenoble, France
Plaats van productieBrussels
UitgeverijIEEE Computer Society
Pagina's1-12
Aantal pagina's12
ISBN van elektronische versie978-1-4799-8710-8
ISBN van geprinte versie 978-1-4799-8711-5
DOI's
StatusGepubliceerd - 23 aug. 2016
Evenement10th IEEE International Conference on Research Challenges in Information Science, IEEE RCIS 2016 - Grenoble, Frankrijk
Duur: 1 mei 20163 mei 2016

Congres

Congres10th IEEE International Conference on Research Challenges in Information Science, IEEE RCIS 2016
Land/RegioFrankrijk
StadGrenoble
Periode1/05/163/05/16

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