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As the global population ages, there is an increasing need for innovative solutions that enable ageing and disabled individuals to live independently and safely in their own homes. This paper presents a comprehensive framework for evaluating AI-driven smart home technologies designed to address this challenge. By leveraging virtual personae and digital simulations, the study provides a methodical approach to testing and comparing various in-home assistance systems, with a focus on fall detection and behavior monitoring. The research involved the creation of a detailed simulation environment that mirrors real-life scenarios, allowing for the rigorous assessment of different technologies. Key aspects such as installation ease, energy consumption, and alert accuracy were analyzed to determine the effectiveness of each solution. The study also developed a robust database of simulated events, including over 300 falls, to further enhance the reliability of the evaluations. Ethical considerations played a crucial role in the selection and assessment process, guided by principles of Responsible Research and Innovation (RRI) and the Eight Caring Technology Principles (8 CTPs). The findings emphasize the importance of user-centered design and ethical development in creating technologies that truly meet the needs of aging populations.

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Assessing AI-Driven Care Solutions for Ageing and Disabled Individuals: A Proposed Framework and Tool

  • 会议论文

  • 发表日期：

    2026年

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  • Nicolas Bioul,
  • Arthur Pisvin,
  • Maxim Lamirande,
  • Jérôme Leclère,
  • Lucas El Raghibi,
  • Adrien Denis,
  • Clementine Schelings,
  • Lara Vigneron,
  • Catherine Elsen,
  • Benoît Macq

摘要

As the global population ages, there is an increasing need for innovative solutions that enable ageing and disabled individuals to live independently and safely in their own homes. This paper presents a comprehensive framework for evaluating AI-driven smart home technologies designed to address this challenge. By leveraging virtual personae and digital simulations, the study provides a methodical approach to testing and comparing various in-home assistance systems, with a focus on fall detection and behavior monitoring. The research involved the creation of a detailed simulation environment that mirrors real-life scenarios, allowing for the rigorous assessment of different technologies. Key aspects such as installation ease, energy consumption, and alert accuracy were analyzed to determine the effectiveness of each solution. The study also developed a robust database of simulated events, including over 300 falls, to further enhance the reliability of the evaluations. Ethical considerations played a crucial role in the selection and assessment process, guided by principles of Responsible Research and Innovation (RRI) and the Eight Caring Technology Principles (8 CTPs). The findings emphasize the importance of user-centered design and ethical development in creating technologies that truly meet the needs of aging populations.