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A Multilayered Contextually Intelligent Activity Recognition Framework for Smart Home

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 1253)

Abstract

The future of Internet of Things (IoT)-based living spaces would involve interaction, coordination, collaboration and communication between humans, machines, robots and other technology-laden systems in the context of users performing their daily routine tasks. Through this Contextually Intelligent Activity Recognition framework, this work proposes to develop a long-term, robust, feasible, easily implementable, sustainable and economic solution for Activity Recognition and Activity Monitoring, that would be able to track, monitor, evaluate, analyze and access human behavior in the context of the multimodal aspects of these user interactions including the spatial and temporal features. This Multilayered Contextually Intelligent Activity Recognition Framework envisions to take a holistic approach to improve the quality of life, enhance the user experience, acceptance and trust on technology during Activities of Daily Living (ADLs), in the context of human-computer, human-machine and human-robot interactions. The results presented uphold the relevance and demonstrate the feasibility for practical implementation of this framework in the future of IoT-based living spaces, for instance Smart Homes and Smart Cities.

Keywords

  • Human-computer interaction
  • Activities of daily living
  • Big data
  • Ubiquitous systems
  • Smart homes
  • Smart cities

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Correspondence to Nirmalya Thakur .

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Thakur, N., Han, C.Y. (2021). A Multilayered Contextually Intelligent Activity Recognition Framework for Smart Home. In: Ahram, T., Taiar, R., Langlois, K., Choplin, A. (eds) Human Interaction, Emerging Technologies and Future Applications III. IHIET 2020. Advances in Intelligent Systems and Computing, vol 1253. Springer, Cham. https://doi.org/10.1007/978-3-030-55307-4_42

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  • DOI: https://doi.org/10.1007/978-3-030-55307-4_42

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