6533b7d4fe1ef96bd1262021
RESEARCH PRODUCT
An Ambient Intelligence System for Assisted Living
Alessandra De PaolaSalvatore GaglioDaniele PeriGiuseppe Lo ReMarco OrtolaniMarco MoranaPierluca Ferrarosubject
QA75ExploitComputer sciencemedia_common.quotation_subjectPopulationAmbient Assisted Living02 engineering and technologyAmbient Assisted Living; Multi-sensor data fusion; Dynamic Bayesian Networks; Context awareness; Rule-based ReasoningDynamic Bayesian NetworkHome automationHuman–computer interaction0202 electrical engineering electronic engineering information engineeringeducationDynamic Bayesian networkmedia_commonSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionieducation.field_of_studyAmbient intelligenceMulti-sensor data fusionbusiness.industryRule-based ReasoningContext awarene020206 networking & telecommunicationsSemantic reasoner020201 artificial intelligence & image processingbusinessRaw dataAutonomydescription
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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2017-12-28 |