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

TLDR

The framework holistically monitors and analyzes human behavior during daily activities. It combines semantic analysis of contextual interactions to identify behavioral patterns with an intelligent decision‑making algorithm that uses these patterns and dynamic contextual and spatial features to detect anomalies, built on HCI, ML, IoT, pattern recognition, and ubiquitous computing. Evaluated on ADL data, the two functionalities achieved 76.71% and 83.87% accuracy, underscoring the framework’s potential to improve the quality of life for the elderly in IoT‑enabled smart homes.

Abstract

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.