Modelling an adjustable autonomous multi-agent internet of things system for elderly smart home

Salama A. Mostafa, Saraswathy Shamini Gunasekaran, Aida Mustapha, Mazin Abed Mohammed, Wafaa Mustafa Abduallah

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Internet of Things (IoT) introduces many intelligent applications that are closely attached to humans’ daily activities. This advanced technology attempts to bridge the gap between the information world and the physical world. Recent studies investigate efficient, flexible, scalable and reliable IoT systems that not only control things and devices on behalf of humans but adaptable to humans’ preferences. However, the autonomous control of the IoT in a smart home or healthcare environment subjects to many factors such as human health, time and date. For example, peoples’ needs and behaviours during workdays differ from weekends or a young person needs and behaviours differs from an elderly person. Hence, the practical setting of a smart home entails flexible management to the autonomous control of IoT systems. This paper proposes an architecture of Adjustable-Autonomous Multi-agent IoT (AAMA-IoT) system to resolve a number of the IoT management of control and application interface challenges. The AAMA-IoT is applied in an elderly smart home simulation in which autonomous agents control passive things such as a chair or door and active things such as a television or an air conditioner. The test results show that the AAMA-IoT system controls 14 things with average activities recognition accuracy of 96.97%.

Original languageEnglish
Title of host publicationAdvances in Neuroergonomics and Cognitive Engineering - Proceedings of the AHFE 2019 International Conference on Neuroergonomics and Cognitive Engineering, and the AHFE International Conference on Industrial Cognitive Ergonomics and Engineering Psychology, 2019
EditorsHasan Ayaz
PublisherSpringer Verlag
Pages301-311
Number of pages11
ISBN (Print)9783030204723
DOIs
Publication statusPublished - 01 Jan 2020
EventAHFE International Conference on Neuroergonomics and Cognitive Engineering, 2019 and the AHFE International Conference on Industrial Cognitive Ergonomics and Engineering Psychology, 2019 - Washington D.C., United States
Duration: 24 Jul 201928 Jul 2019

Publication series

NameAdvances in Intelligent Systems and Computing
Volume953
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

ConferenceAHFE International Conference on Neuroergonomics and Cognitive Engineering, 2019 and the AHFE International Conference on Industrial Cognitive Ergonomics and Engineering Psychology, 2019
CountryUnited States
CityWashington D.C.
Period24/07/1928/07/19

Fingerprint

Autonomous agents
Internet of things
Television
Health
Control systems
Air

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Mostafa, S. A., Gunasekaran, S. S., Mustapha, A., Mohammed, M. A., & Abduallah, W. M. (2020). Modelling an adjustable autonomous multi-agent internet of things system for elderly smart home. In H. Ayaz (Ed.), Advances in Neuroergonomics and Cognitive Engineering - Proceedings of the AHFE 2019 International Conference on Neuroergonomics and Cognitive Engineering, and the AHFE International Conference on Industrial Cognitive Ergonomics and Engineering Psychology, 2019 (pp. 301-311). (Advances in Intelligent Systems and Computing; Vol. 953). Springer Verlag. https://doi.org/10.1007/978-3-030-20473-0_29
Mostafa, Salama A. ; Gunasekaran, Saraswathy Shamini ; Mustapha, Aida ; Mohammed, Mazin Abed ; Abduallah, Wafaa Mustafa. / Modelling an adjustable autonomous multi-agent internet of things system for elderly smart home. Advances in Neuroergonomics and Cognitive Engineering - Proceedings of the AHFE 2019 International Conference on Neuroergonomics and Cognitive Engineering, and the AHFE International Conference on Industrial Cognitive Ergonomics and Engineering Psychology, 2019. editor / Hasan Ayaz. Springer Verlag, 2020. pp. 301-311 (Advances in Intelligent Systems and Computing).
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Mostafa, SA, Gunasekaran, SS, Mustapha, A, Mohammed, MA & Abduallah, WM 2020, Modelling an adjustable autonomous multi-agent internet of things system for elderly smart home. in H Ayaz (ed.), Advances in Neuroergonomics and Cognitive Engineering - Proceedings of the AHFE 2019 International Conference on Neuroergonomics and Cognitive Engineering, and the AHFE International Conference on Industrial Cognitive Ergonomics and Engineering Psychology, 2019. Advances in Intelligent Systems and Computing, vol. 953, Springer Verlag, pp. 301-311, AHFE International Conference on Neuroergonomics and Cognitive Engineering, 2019 and the AHFE International Conference on Industrial Cognitive Ergonomics and Engineering Psychology, 2019, Washington D.C., United States, 24/07/19. https://doi.org/10.1007/978-3-030-20473-0_29

Modelling an adjustable autonomous multi-agent internet of things system for elderly smart home. / Mostafa, Salama A.; Gunasekaran, Saraswathy Shamini; Mustapha, Aida; Mohammed, Mazin Abed; Abduallah, Wafaa Mustafa.

Advances in Neuroergonomics and Cognitive Engineering - Proceedings of the AHFE 2019 International Conference on Neuroergonomics and Cognitive Engineering, and the AHFE International Conference on Industrial Cognitive Ergonomics and Engineering Psychology, 2019. ed. / Hasan Ayaz. Springer Verlag, 2020. p. 301-311 (Advances in Intelligent Systems and Computing; Vol. 953).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Mostafa SA, Gunasekaran SS, Mustapha A, Mohammed MA, Abduallah WM. Modelling an adjustable autonomous multi-agent internet of things system for elderly smart home. In Ayaz H, editor, Advances in Neuroergonomics and Cognitive Engineering - Proceedings of the AHFE 2019 International Conference on Neuroergonomics and Cognitive Engineering, and the AHFE International Conference on Industrial Cognitive Ergonomics and Engineering Psychology, 2019. Springer Verlag. 2020. p. 301-311. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-3-030-20473-0_29