The recent advancement and development of computer electronic devices has led to the
adoption of smart home sensing systems, stimulating the demand for associated products …

Human activity recognition using smart home sensors is one of the bases of ubiquitous
computing in smart environments and a topic undergoing intense research in the field of …

Human Activity Recognition (HAR) employing inertial motion data has gained considerable
momentum in recent years, both in research and industrial applications. From the abstract …

Abstract Convolutional Neural Networks (CNN) are very useful for fully automatic extraction
of discriminative features from raw sensor data. This is an important problem in activity …

The ability to identify and accurately predict abnormal behavior is important for health
monitoring systems in smart environments. Specifically, for elderly persons wishing to …

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 …

Human Activity Recognition (HAR) is a field that infers human activities from raw time-series
signals acquired through embedded sensors of smartphones and wearable devices. It has …

A smart home, which is an extension of a traditional home, is equipped with ubiquitous
sensors embedded in consumer appliances, connected via sensing technologies such as …

Recent advances in Internet of Things (IoT) technologies and the reduction in the cost of
sensors have encouraged the development of smart environments, such as smart homes …

In this paper, we focus on data-driven approaches to human activity recognition (HAR). Data-
driven approaches rely on good quality data during training, however, a shortage of high …