Activity Monitoring Process based on Model-Driven Engineering – Application to Ambient Assisted Living

The supervisor of the activities of a system user should benefit from the knowledge contained in the event logs of the user. They allow the monitoring of the sequential and parallel user activities. To make event logs more accessible to the supervisor, we suggest a process mining approach, including...

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Bibliographic Details
Main Authors: Simonin Jacques, Soulas Julie, Lenca Philippe
Format: Article
Language:English
Published: De Gruyter 2015-08-01
Series:Journal of Intelligent Systems
Subjects:
Online Access:https://doi.org/10.1515/jisys-2014-0143
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spelling doaj-1a533c47ecf641f4a798f7691ab6cee02021-09-06T19:40:36ZengDe GruyterJournal of Intelligent Systems0334-18602191-026X2015-08-0124337138210.1515/jisys-2014-0143Activity Monitoring Process based on Model-Driven Engineering – Application to Ambient Assisted LivingSimonin Jacques0Soulas Julie1Lenca Philippe2Institute Mines-Telecom, Télécom Bretagne, UMR CNRS 6285, Lab-STICC, Université Européenne de Bretagne, 29238 Brest, FranceInstitute Mines-Telecom, Télécom Bretagne, UMR CNRS 6285, Lab-STICC, Université Européenne de Bretagne, 29238 Brest, FranceInstitute Mines-Telecom, Télécom Bretagne, UMR CNRS 6285, Lab-STICC, Université Européenne de Bretagne, 29238 Brest, FranceThe supervisor of the activities of a system user should benefit from the knowledge contained in the event logs of the user. They allow the monitoring of the sequential and parallel user activities. To make event logs more accessible to the supervisor, we suggest a process mining approach, including first the design of an understanding model of the activities of a system user. The model design is based on the relationships between the event logs and the activities of a system user. An intervention model completes the understanding model to assist the supervisor. The intervention model enables an action of the supervisor on the critical activities, and the detection of anomalies. The models are automatically designed with a model-driven engineering approach. An experiment on a smart home system illustrates this tooled design, where the supervisor is a medical or paramedical staff member.https://doi.org/10.1515/jisys-2014-0143monitoring processevent logunderstanding modelintervention modelmodel-driven engineering93a3091b7497k80
collection DOAJ
language English
format Article
sources DOAJ
author Simonin Jacques
Soulas Julie
Lenca Philippe
spellingShingle Simonin Jacques
Soulas Julie
Lenca Philippe
Activity Monitoring Process based on Model-Driven Engineering – Application to Ambient Assisted Living
Journal of Intelligent Systems
monitoring process
event log
understanding model
intervention model
model-driven engineering
93a30
91b74
97k80
author_facet Simonin Jacques
Soulas Julie
Lenca Philippe
author_sort Simonin Jacques
title Activity Monitoring Process based on Model-Driven Engineering – Application to Ambient Assisted Living
title_short Activity Monitoring Process based on Model-Driven Engineering – Application to Ambient Assisted Living
title_full Activity Monitoring Process based on Model-Driven Engineering – Application to Ambient Assisted Living
title_fullStr Activity Monitoring Process based on Model-Driven Engineering – Application to Ambient Assisted Living
title_full_unstemmed Activity Monitoring Process based on Model-Driven Engineering – Application to Ambient Assisted Living
title_sort activity monitoring process based on model-driven engineering – application to ambient assisted living
publisher De Gruyter
series Journal of Intelligent Systems
issn 0334-1860
2191-026X
publishDate 2015-08-01
description The supervisor of the activities of a system user should benefit from the knowledge contained in the event logs of the user. They allow the monitoring of the sequential and parallel user activities. To make event logs more accessible to the supervisor, we suggest a process mining approach, including first the design of an understanding model of the activities of a system user. The model design is based on the relationships between the event logs and the activities of a system user. An intervention model completes the understanding model to assist the supervisor. The intervention model enables an action of the supervisor on the critical activities, and the detection of anomalies. The models are automatically designed with a model-driven engineering approach. An experiment on a smart home system illustrates this tooled design, where the supervisor is a medical or paramedical staff member.
topic monitoring process
event log
understanding model
intervention model
model-driven engineering
93a30
91b74
97k80
url https://doi.org/10.1515/jisys-2014-0143
work_keys_str_mv AT simoninjacques activitymonitoringprocessbasedonmodeldrivenengineeringapplicationtoambientassistedliving
AT soulasjulie activitymonitoringprocessbasedonmodeldrivenengineeringapplicationtoambientassistedliving
AT lencaphilippe activitymonitoringprocessbasedonmodeldrivenengineeringapplicationtoambientassistedliving
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