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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Online Access: | https://doi.org/10.1515/jisys-2014-0143 |
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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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1717768098273034240 |