Authors:
Zaineb Liouane
1
;
Tayeb Lemlouma
2
;
Philippe Roose
3
;
Fréderic Weis
2
and
Hassani Messaoud
1
Affiliations:
1
Monastir University, Tunisia
;
2
Rennes1 University, France
;
3
Pau and the Adour Contries University, France
Keyword(s):
Smart Home, Elderly Person, Home by Room Activities Language, Hierarchical and Hidden Markov Model, Activities, Scenarios, Prediction.
Related
Ontology
Subjects/Areas/Topics:
Aggregation, Classification and Tracking
;
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Data Manipulation
;
Data Quality and Integrity
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Methodologies and Methods
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Reasoning on Sensor Data
;
Sensor Data Fusion
;
Sensor Networks
;
Soft Computing
Abstract:
Recognizing activities of daily living plays an important role in healthcare. It is necessary to use an adapted model to simulate the human behavior in a domestic space to monitor the patient harmonically and to intervene in the necessary time. In this paper we tackle this problem using the hierarchical hidden Markov model for representing and recognizing complex indoor activities, we propose a new grammar “Home By Room Activities language” to facilitate the complexity of human scenarios and hold us account to the abnormal activities.