Nowadays, the population’s average age is constantly increasing, and thus the need for specialized home assistance is on the rise. Smart homes especially tailored to meet elderly and disabled people's needs can help them maintaining their autonomy, whilst ensuring their safety and well-being. This paper proposes a complete context-aware system for Ambient Assisted Living (AAL), which infers user's actions and context, analyzing its past and current behavior to detect anomalies and prevent possible emergencies. The proposed system exploits Dynamic Bayesian Networks to merge raw data coming from heterogeneous sensors and infer user's behavior and health conditions. A rule-based reasoner is able to detect and predict anomalies in such data, sending appropriate alerts to caregivers and family members. The effectiveness of the proposed AAL system is demonstrated by extensive experimental results carried out in a simulated smart home.

De Paola, A., Ferraro, P., Gaglio, S., Lo Re, G., Morana, M., Ortolani, M., et al. (2017). An Ambient Intelligence System for Assisted Living. In Proceedings of the International Annual Conference of AEIT (2017). IEEE [10.23919/AEIT.2017.8240559].

An Ambient Intelligence System for Assisted Living

De Paola, Alessandra;Ferraro, Pierluca;Gaglio, Salvatore;Lo Re, Giuseppe;Morana, Marco;Ortolani, Marco;Peri, Daniele
2017-01-01

Abstract

Nowadays, the population’s average age is constantly increasing, and thus the need for specialized home assistance is on the rise. Smart homes especially tailored to meet elderly and disabled people's needs can help them maintaining their autonomy, whilst ensuring their safety and well-being. This paper proposes a complete context-aware system for Ambient Assisted Living (AAL), which infers user's actions and context, analyzing its past and current behavior to detect anomalies and prevent possible emergencies. The proposed system exploits Dynamic Bayesian Networks to merge raw data coming from heterogeneous sensors and infer user's behavior and health conditions. A rule-based reasoner is able to detect and predict anomalies in such data, sending appropriate alerts to caregivers and family members. The effectiveness of the proposed AAL system is demonstrated by extensive experimental results carried out in a simulated smart home.
2017
Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni
978-8-8872-3737-5
De Paola, A., Ferraro, P., Gaglio, S., Lo Re, G., Morana, M., Ortolani, M., et al. (2017). An Ambient Intelligence System for Assisted Living. In Proceedings of the International Annual Conference of AEIT (2017). IEEE [10.23919/AEIT.2017.8240559].
File in questo prodotto:
File Dimensione Formato  
08240559 (1).pdf

Solo gestori archvio

Descrizione: Articolo
Tipologia: Versione Editoriale
Dimensione 1.39 MB
Formato Adobe PDF
1.39 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
aeit_front_TOC_authors.pdf

Solo gestori archvio

Descrizione: Front page e TOC
Tipologia: Altro materiale (es. dati della ricerca)
Dimensione 519.19 kB
Formato Adobe PDF
519.19 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/250726
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 19
  • ???jsp.display-item.citation.isi??? 0
social impact