Automated Generation of Models of Activities of Daily Living

Abstract : In order to increase the safety of autonomous elderly people in their home, Ambient Assisted Living technologies are currently emerging. Namely, the recognition of their activities might be a way to detect eventual health problems, and can be performed in a Smarthome equipped with binary sensors. Hence, this communication aims at providing means to automatically generate a formal model of the Activities of Daily Living. A data mining approach in order to discover frequent habits of the observed inhabitant from a database of sequences of sensor events is proposed. Those frequent habits are then formally modelled using finite automata, leading to the construction of a map of habits mirroring the behaviour of the inhabitant. Such a model could then be used for online identification of habits, and even predictions of the upcoming behaviour. Results obtained on a case study are also presented.
Document type :
Conference papers
Complete list of metadatas

Cited literature [19 references]  Display  Hide  Download
Contributor : Jérémie Saives <>
Submitted on : Tuesday, June 3, 2014 - 4:17:02 PM
Last modification on : Thursday, February 9, 2017 - 3:53:58 PM
Long-term archiving on : Wednesday, September 3, 2014 - 12:35:10 PM


Files produced by the author(s)


  • HAL Id : hal-00999505, version 1



Jérémie Saives, Gregory Faraut. Automated Generation of Models of Activities of Daily Living. 12th International Workshop on Discrete Event Systems-WODES 2014, May 2014, Cachan, France. pp.13-20. ⟨hal-00999505⟩



Record views


Files downloads