AIoT for aging in place: from theory to practice

The rapidly aging global population necessitates solutions to support the growing preference among seniors to age in place. This thesis presents a novel integration of the Person-Environment (P-E) Fit theory with Artificial Intelligence of Things (AIoT) to guide aging in place (AIP) system design, f...

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Main Author: Zhang, Huiguo
Other Authors: Vun Chan Hua, Nicholas
Format: Thesis-Doctor of Philosophy
Language:English
Published: Nanyang Technological University 2024
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Online Access:https://hdl.handle.net/10356/175547
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1755472024-05-03T15:39:51Z AIoT for aging in place: from theory to practice Zhang, Huiguo Vun Chan Hua, Nicholas School of Computer Science and Engineering ASCHVUN@ntu.edu.sg Computer and Information Science Aging in place Artificial intelligence of things Person-environment (P-E) fit theory The rapidly aging global population necessitates solutions to support the growing preference among seniors to age in place. This thesis presents a novel integration of the Person-Environment (P-E) Fit theory with Artificial Intelligence of Things (AIoT) to guide aging in place (AIP) system design, focusing on personalized, privacy-preserving solutions that allow elderly individuals to live independently while ensuring their safety and well-being. Based on the foundation of the P-E Fit theory, we introduce a comprehensive P-E for AIP model (PE4AIP) that assesses elderly well-being through three primary dimensions: person characteristics, environment characteristics, and person-environment interactions. The model identifies key P-E fit indicators, such as motion, lifestyle regularity, social interactions, and environmental comfort, which are essential for quantifying the `fit' between seniors and their environments. To operationalize this model, a PE4AIP-enabled AIP design architecture was developed, guiding the creation of AIP systems with a emphasis on privacy and personalization. Notably, the developed architecture incorporates innovative technologies for real-time monitoring and data processing, including a non-intrusive fall detection system using ambient sensors and edge computing, and a unique notification system using 3D animation to communicate the status of the elderly to caregivers without compromising privacy. Empirical studies and experiments validate the effectiveness of the proposed model and the architecture. A implementation of the Smart Aging in Place System (SAIPS) demonstrated the practicality and acceptance of the system among elderly participants and their caregivers. The results highlight the system’s accuracy in predicting well-being, its unobtrusiveness, and the overall positive reception of the technology. This research advances gerontechnology by offering a theoretically grounded and empirically validated framework that enhances the independence and quality of life for the elderly. The breadth and depth of our work stand as a meaningful contribution to the development of intelligent, practical, and effective aging-in-place solutions, with wide-reaching implications for the continually evolving field of assistive technology for older adults. Doctor of Philosophy 2024-04-29T05:18:40Z 2024-04-29T05:18:40Z 2024 Thesis-Doctor of Philosophy Zhang, H. (2024). AIoT for aging in place: from theory to practice. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/175547 https://hdl.handle.net/10356/175547 10.32657/10356/175547 en This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Computer and Information Science
Aging in place
Artificial intelligence of things
Person-environment (P-E) fit theory
spellingShingle Computer and Information Science
Aging in place
Artificial intelligence of things
Person-environment (P-E) fit theory
Zhang, Huiguo
AIoT for aging in place: from theory to practice
description The rapidly aging global population necessitates solutions to support the growing preference among seniors to age in place. This thesis presents a novel integration of the Person-Environment (P-E) Fit theory with Artificial Intelligence of Things (AIoT) to guide aging in place (AIP) system design, focusing on personalized, privacy-preserving solutions that allow elderly individuals to live independently while ensuring their safety and well-being. Based on the foundation of the P-E Fit theory, we introduce a comprehensive P-E for AIP model (PE4AIP) that assesses elderly well-being through three primary dimensions: person characteristics, environment characteristics, and person-environment interactions. The model identifies key P-E fit indicators, such as motion, lifestyle regularity, social interactions, and environmental comfort, which are essential for quantifying the `fit' between seniors and their environments. To operationalize this model, a PE4AIP-enabled AIP design architecture was developed, guiding the creation of AIP systems with a emphasis on privacy and personalization. Notably, the developed architecture incorporates innovative technologies for real-time monitoring and data processing, including a non-intrusive fall detection system using ambient sensors and edge computing, and a unique notification system using 3D animation to communicate the status of the elderly to caregivers without compromising privacy. Empirical studies and experiments validate the effectiveness of the proposed model and the architecture. A implementation of the Smart Aging in Place System (SAIPS) demonstrated the practicality and acceptance of the system among elderly participants and their caregivers. The results highlight the system’s accuracy in predicting well-being, its unobtrusiveness, and the overall positive reception of the technology. This research advances gerontechnology by offering a theoretically grounded and empirically validated framework that enhances the independence and quality of life for the elderly. The breadth and depth of our work stand as a meaningful contribution to the development of intelligent, practical, and effective aging-in-place solutions, with wide-reaching implications for the continually evolving field of assistive technology for older adults.
author2 Vun Chan Hua, Nicholas
author_facet Vun Chan Hua, Nicholas
Zhang, Huiguo
format Thesis-Doctor of Philosophy
author Zhang, Huiguo
author_sort Zhang, Huiguo
title AIoT for aging in place: from theory to practice
title_short AIoT for aging in place: from theory to practice
title_full AIoT for aging in place: from theory to practice
title_fullStr AIoT for aging in place: from theory to practice
title_full_unstemmed AIoT for aging in place: from theory to practice
title_sort aiot for aging in place: from theory to practice
publisher Nanyang Technological University
publishDate 2024
url https://hdl.handle.net/10356/175547
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