A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Digital Twin Models Supporting Cognitive Buildings for Ambient Assisted Living
The rapid and global aging of population is outlining the need for environments that can provide support for these individuals during their daily activities. The challenge of an aging society is being addressed through the incorporation of new technologies into the home environment, which is nothing less than Ambient Assisted Living (AAL). To date, some of the AAL solutions exploit AI models to recognize the elderly’s behaviors through data collected by sensors. In recent times, Digital Twins (DTs) at building level have begun to appear on the construction domain. These are still under development but through the integration of users into assessments, they improve efficiency, prevention, and prediction of likely events through real-time AI computing. The integration of DT and AAL defines cognitive buildings which aim to learn at scale, reason with a purpose, and co-operate with users in a natural way. This research aims to develop DT models to achieve scenario awareness to provide support to elderly people living alone and suffering from cognitive disorders. The proposed multi-agent architecture is based on a five-layer system that autonomously develops high-level knowledge to detect anomalies in the home environment scenarios and therefore support the user. Bayesian networks (BNs) are exploited to perform high-level deductive reasoning on low-level multi-modal information, thus recognizing senseless or dangerous behaviors, environmental disruptions, changes in behavioral patterns, and serious medical events. Bi-directional user-system interaction provides user support by leveraging Speech-To-Text and Text-To-Speech AI agents. Three main functions were tested: real-time data integration, anomaly detection, and two-way interaction.
Digital Twin Models Supporting Cognitive Buildings for Ambient Assisted Living
The rapid and global aging of population is outlining the need for environments that can provide support for these individuals during their daily activities. The challenge of an aging society is being addressed through the incorporation of new technologies into the home environment, which is nothing less than Ambient Assisted Living (AAL). To date, some of the AAL solutions exploit AI models to recognize the elderly’s behaviors through data collected by sensors. In recent times, Digital Twins (DTs) at building level have begun to appear on the construction domain. These are still under development but through the integration of users into assessments, they improve efficiency, prevention, and prediction of likely events through real-time AI computing. The integration of DT and AAL defines cognitive buildings which aim to learn at scale, reason with a purpose, and co-operate with users in a natural way. This research aims to develop DT models to achieve scenario awareness to provide support to elderly people living alone and suffering from cognitive disorders. The proposed multi-agent architecture is based on a five-layer system that autonomously develops high-level knowledge to detect anomalies in the home environment scenarios and therefore support the user. Bayesian networks (BNs) are exploited to perform high-level deductive reasoning on low-level multi-modal information, thus recognizing senseless or dangerous behaviors, environmental disruptions, changes in behavioral patterns, and serious medical events. Bi-directional user-system interaction provides user support by leveraging Speech-To-Text and Text-To-Speech AI agents. Three main functions were tested: real-time data integration, anomaly detection, and two-way interaction.
Digital Twin Models Supporting Cognitive Buildings for Ambient Assisted Living
The Urban Book Series
Arbizzani, Eugenio (editor) / Cangelli, Eliana (editor) / Clemente, Carola (editor) / Cumo, Fabrizio (editor) / Giofrè, Francesca (editor) / Giovenale, Anna Maria (editor) / Palme, Massimo (editor) / Paris, Spartaco (editor) / Corneli, Alessandra (author) / Binni, Leonardo (author)
International Conference on Technological Imagination in the Green and Digital Transition ; 2022 ; Rome, Italy
2023-06-30
12 pages
Article/Chapter (Book)
Electronic Resource
English
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