A Genetic Neural Network Approach for Unusual Behavior Prediction in Smart Home

Zaineb Liouane (1) , Tayeb Lemlouma (2) , Philippe Roose (3) , Frédéric Weis (4) , Hassani Messaoud (1)

1 ENIM - École Nationale d’Ingénieurs de Monastir
2 IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires
3 LIUPPA - Laboratoire Informatique de l'Université de Pau et des Pays de l'Adour
4 TACOMA - TAngible COMputing Architectures

Detect efficiently the activities of daily living of elderly people at home in order to provide a secure life and to intervene in the necessary time is an important problem we propose here an improved artificial neural network model. As we need an efficient prediction model, we propose a recurrent output neural network model (RO-NN) combined with a genetic algorithm (GA) which surely monitors and predicts the state of the concerned elderly person. Furthermore, we propose a prediction algorithm “Unusual Behavior Algorithm (UBA)” dedicated to detect the unusual activities and hold us account in the dangerous state.

Mots clés: Sensors; Smart spaces; Elderly; Unusual Behavior Algorithm; Abrnomal behavior; Recurrent Output Neural Network

Domaines: Réseaux et télécommunications [cs.NI]; Intelligence artificielle [cs.AI]; Environnements Informatiques pour l'Apprentissage Humain; Apprentissage [cs.LG]; Réseau de neurones [cs.NE]; Santé publique et épidémiologie

Zaineb Liouane, Tayeb Lemlouma, Philippe Roose, Frédéric Weis, Hassani Messaoud. A Genetic Neural Network Approach for Unusual Behavior Prediction in Smart Home. 16th International Conference on Intelligent Systems Design and Applications, Dec 2016, Porto, Portugal. pp.738-748, ⟨10.1007/978-3-319-53480-0_73⟩. ⟨hal-01462993⟩