Abstract Various Human Activities are classified through time-series data generated by the
sensors of wearable devices. Many real-time scenarios such as Healthcare Surveillance …

Advances in smart home technology and IoT devices had made us capable of monitoring
human activities in a non-intrusive way. This data, in turn, enables us to predict the health …

In this era, deep learning methods offer a broad spectrum of efficient and original algorithms
to recognize or predict an output when given a sequence of inputs. In current trends, deep …

Many smart home applications rely on indoor human activity recognition. This challenge is
currently primarily tackled by employing video camera sensors. However, the use of such …

Human Activity Recognition (HAR) is a field that uses collected data to classify different
human actions. One simple and general approach to HAR is to use the sensor data from a …

Human activity recognition is concerned with detecting different types of human movements
and actions using data gathered from various types of sensors. Deep learning approaches …

Abstract Human Activity Recognition (HAR) has become a crucial area of research, driven
by the advancements in wearable device sensors. HAR finds widespread applications …

Human activity recognition (HAR) is an important technology in pervasive computing
because it can be applied to many real-life, human-centric problems such as eldercare and …

Human activity recognition (HAR) based on time series data is the problem of classifying
various patterns. Its widely applications in health care owns huge commercial benefit. With …

Human activities are inherently translation invariant and hierarchical. Human activity
recognition (HAR), a field that has garnered a lot of attention in recent years due to its high …