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Multi-Agent Interaction to Assist Visually-Impaired and Elderly People

Author

Listed:
  • Juliana Damasio Oliveira

    (School of Technology, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre 90619-900, Brazil)

  • Debora C. Engelmann

    (School of Technology, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre 90619-900, Brazil
    Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, 16145 Genoa, Italy)

  • Davi Kniest

    (School of Technology, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre 90619-900, Brazil)

  • Renata Vieira

    (CIDEHUS, University of Évora, 7000-809 Évora, Portugal)

  • Rafael H. Bordini

    (School of Technology, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre 90619-900, Brazil)

Abstract

A voice-controlled smart home system based on conversational agents can address the specific needs of older people, proactively providing support, compensating for cognitive decline, and coping with solitude, among other features. In particular, Multi-Agent Systems (MAS) platforms provide considerable support for complex adaptive systems that are naturally distributed and situated in dynamic environments, such as Ambient intelligence (AmI) applications. Such autonomous intelligent agents are capable of independent reasoning and joint analysis of complex situations to support high-level interaction with humans, besides providing typical characteristics of MAS, such as cooperation and coordinated action. In this context, we developed an approach using a MAS previously evaluated for visually impaired users, where most of the system’s functionalities are also helpful for the elderly. Our methodology is based on the four steps of the interactive design process. As a result, we determined that our approach has elements that allow for natural interaction with users, and we identified and discussed improvements and new features for future work. We believe that our findings can point to directions for building AmI systems that are capable of more natural interaction with users.

Suggested Citation

  • Juliana Damasio Oliveira & Debora C. Engelmann & Davi Kniest & Renata Vieira & Rafael H. Bordini, 2022. "Multi-Agent Interaction to Assist Visually-Impaired and Elderly People," IJERPH, MDPI, vol. 19(15), pages 1-14, July.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:15:p:8945-:d:869664
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    Citations

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    Cited by:

    1. Toshiharu Igarashi & Katsuya Iijima & Kunio Nitta & Yu Chen, 2024. "Detailed Analysis of Responses from Older Adults through Natural Speech: Comparison of Questions by AI Agents and Humans," IJERPH, MDPI, vol. 21(9), pages 1-15, September.
    2. Ting Huang & Chengmin Zhou & Xin Luo & Jake Kaner, 2022. "Study of Ageing in Complex Interface Interaction Tasks: Based on Combined Eye-Movement and HRV Bioinformatic Feedback," IJERPH, MDPI, vol. 19(24), pages 1-12, December.

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