A significant challenge to provide services to the inhabitant in a smart environment resides
in the effective implementation of models. Most of the proposed models are conceptual and …

Activity recognition has become a popular research branch in the field of pervasive
computing in recent years. A large number of experiments can be obtained that activity …

To solve the limitation problem of traditional human activity recognition (HAR) tasks which
use features extracted manually and some shallow machine learning models, a novel multi …

The study of human regular tasks have become more prevalent and accessible as a result of
the widespread use of different sensors integrated into mobile devices. This issue now exists …

Human activity recognition is still a challenging problem in particular environment. In this
paper, we propose a novel method based on wearable sensors to effectively recognize the …

Human activity recognition has become an active research field over the past few years due
to its wide application in various fields such as health-care, smart home monitoring, and …

Background & Objective: This paper proposes a Fourier transform inspired method to
classify human activities from time series sensor data. Methods: Our method begins by …

Multi-modal data extracted from different sensors in a smart home can be fused to build
models that recognize the daily living activities of residents. This paper proposes a Deep …

With a widespread of various sensors embedded in mobile devices, the analysis of human
daily activities becomes more common and straightforward. This task now arises in a range …

Activity recognition is an important step towards automatically measuring the functional
health of individuals in smart home settings. Since the inherent nature of human activities is …