Activity detection and classification using different sensor modalities have emerged as
revolutionary technology for real-time and autonomous monitoring in behaviour analysis …

In Ambient Intelligence (AmI), the activity a user is engaged in is an essential part of the
context, so its recognition is of paramount importance for applications in areas like sports …

This paper compares the three levels of data fusion with the goal of determining the optimal
level of data fusion for multi-sensor human activity data. Using the data processing pipeline …

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 …

Multi-sensor fusion refers to methods used for combining information coming from several
sensors (in some cases, different ones) with the aim to make one sensor compensate for the …

Recognition of human actions in partially cluttered environments is an important research
field of computer vision and human-computer interaction. This field has recently garnered …

Multimodal sensors in healthcare applications have been increasingly researched because
it facilitates automatic and comprehensive monitoring of human behaviors, high-intensity …

Advancement in smart sensing and computing technologies has provided a dynamic
opportunity to develop intelligent systems for human activity monitoring and thus assisted …

Recently it has been noted that user behaviour can have a large impact on the final energy
consumption in buildings. Through the combination of mathematical modelling and data …

Lately, many scientists have focused their research on subjects like smart buildings, sensor
devices, virtual sensing, buildings management, Internet of Things (IoT), artificial intelligence …