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Article

An Ambient Intelligence-Based Human Behavior Monitoring Framework for Ubiquitous Environments

Department of Electrical Engineering and Computer Science, University of Cincinnati, Cincinnati, OH 45221-0030, USA
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Author to whom correspondence should be addressed.
Academic Editor: Spyros Panagiotakis
Information 2021, 12(2), 81; https://doi.org/10.3390/info12020081
Received: 21 January 2021 / Revised: 7 February 2021 / Accepted: 10 February 2021 / Published: 14 February 2021
(This article belongs to the Special Issue Pervasive Computing in IoT)
This framework for human behavior monitoring aims to take a holistic approach to study, track, monitor, and analyze human behavior during activities of daily living (ADLs). The framework consists of two novel functionalities. First, it can perform the semantic analysis of user interactions on the diverse contextual parameters during ADLs to identify a list of distinct behavioral patterns associated with different complex activities. Second, it consists of an intelligent decision-making algorithm that can analyze these behavioral patterns and their relationships with the dynamic contextual and spatial features of the environment to detect any anomalies in user behavior that could constitute an emergency. These functionalities of this interdisciplinary framework were developed by integrating the latest advancements and technologies in human–computer interaction, machine learning, Internet of Things, pattern recognition, and ubiquitous computing. The framework was evaluated on a dataset of ADLs, and the performance accuracies of these two functionalities were found to be 76.71% and 83.87%, respectively. The presented and discussed results uphold the relevance and immense potential of this framework to contribute towards improving the quality of life and assisted living of the aging population in the future of Internet of Things (IoT)-based ubiquitous living environments, e.g., smart homes. View Full-Text
Keywords: ambient intelligence; human behavior monitoring; smart homes; activities of daily living; elderly population; machine learning; internet of things; ubiquitous computing ambient intelligence; human behavior monitoring; smart homes; activities of daily living; elderly population; machine learning; internet of things; ubiquitous computing
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MDPI and ACS Style

Thakur, N.; Han, C.Y. An Ambient Intelligence-Based Human Behavior Monitoring Framework for Ubiquitous Environments. Information 2021, 12, 81. https://doi.org/10.3390/info12020081

AMA Style

Thakur N, Han CY. An Ambient Intelligence-Based Human Behavior Monitoring Framework for Ubiquitous Environments. Information. 2021; 12(2):81. https://doi.org/10.3390/info12020081

Chicago/Turabian Style

Thakur, Nirmalya, and Chia Y. Han. 2021. "An Ambient Intelligence-Based Human Behavior Monitoring Framework for Ubiquitous Environments" Information 12, no. 2: 81. https://doi.org/10.3390/info12020081

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