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A Multilayered Contextually Intelligent Activity Recognition Framework for Smart Home

  • Nirmalya ThakurEmail author
  • Chia Y. Han
Conference paper
  • 295 Downloads
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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Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

Authors and Affiliations

  1. 1.Department of Electrical Engineering and Computer ScienceUniversity of CincinnatiCincinnatiUSA

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