A Decision-Aware Ambient Assisted Living System with IoT Embedded Device for In-Home Monitoring of Older Adults

Area of Science:

• Computer Science
• Gerontology
• Human-Computer Interaction

Background:

• Independent living for older adults is challenged by memory impairments and decision-making difficulties.
• Assisted living systems require innovative solutions to support seniors and their caregivers effectively.
• Current technologies often lack integrated approaches for real-time monitoring and personalized assistance.

Purpose of the Study:

• To propose an integrated conceptual model for assisted living systems tailored for older adults with mild memory impairments.
• To develop a proof-of-concept implementation to evaluate the feasibility and effectiveness of the proposed model.
• To enhance the independent living capabilities of older adults and support their caregivers.

Main Methods:

• An integrated model comprising an indoor location unit, augmented reality (AR) application, IoT-based fuzzy decision-making system, and a caregiver interface.
• Proof-of-concept implementation and functional experiments based on factual scenarios.
• Evaluation of system accuracy and response time.

Main Results:

• The proof-of-concept implementation demonstrated the feasibility of the proposed assisted living system.
• Functional experiments validated the effectiveness of the integrated approach in supporting older adults and caregivers.
• The system achieved acceptable accuracy and response times in experimental scenarios.

Conclusions:

• The proposed integrated system is feasible and has significant potential to promote scalable and customizable assisted living.
• Implementing such systems can effectively reduce the challenges associated with independent living for older adults.
• This technology offers a promising avenue for enhancing the quality of life for seniors with cognitive impairments.