In the last decade, Human Activity Recognition (HAR) has become a vibrant research area,
especially due to the spread of electronic devices such as smartphones, smartwatches and …

Abstract The use of Convolutional Neural Networks (CNNs) as a feature learning method for
Human Activity Recognition (HAR) is becoming more and more common. Unlike …

Current Virtual Reality systems typically use cameras to capture user input from controllers
or free-hand mid-air interaction. In this paper, we argue that this is a key impediment to …

The IoT describes a development field where new approaches and trends are in constant
change. In this scenario, new devices and sensors are offering higher precision in everyday …

Postural changes while maintaining a correct body position are the most efficient method of
preventing pressure ulcers. However, executing a protocol of postural changes over a long …

The classic models used to predict the behavior of photovoltaic systems, which are based on
the physical process of the solar cell, are limited to defining the analytical equation to obtain …

The IoT describes a development field where new approaches and trends are in constant
change. In this scenario, new devices and sensors are offering higher precision in everyday …

Currently, Human Activity Recognition (HAR) applications need a large volume of data to be
able to generalize to new users and environments. However, the availability of labeled data …

Deep learning techniques such as Convolutional Neural Networks (CNNs) have shown
good results in activity recognition. One of the advantages of using these methods resides in …

The recent advancements in sensing technology have opened up the possibilities for
various services that support daily life, such as energy-saving home appliance control. To …