Development of digital twin models supporting ambient assisted living
DOI: 10.35490/EC3.2022.180
Abstract: World population aging requires finding solutions to improve independent living options. Ambient Assisted Living (AAL) is making step forward developing services supporting the elderly, but the implementation of predictive environments is still far away. Besides, the emerging Digital Twin (DT) concept has begun to shape the first cognitive environments that integrate users into assessments, improving efficiency, prevention, and prediction of likely events through real-time AI computing. This paper provides a prototype of a Cognitive Building framework based on DT models that develop high-level knowledge to achieve real-time Scenario Awareness and offer appropriate AAL services once anomalous scenarios are detected.
Keywords: Activity Recognition, Ambient Assisted Living, Bayesian Networks, Digital Twin, Scenario Awareness