Advances in smart home technology and IoT devices has enabled us for monitoring of
human activities for their health status and efficient energy consumption. Machine learning …

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 …

Multi-sensor based human activity recognition is one of the challenges in the ambient
intelligent environments such as smart home and smart city. Ordinary people in their daily …

Recognizing the activities of daily living (ADLs) for a multi-person residence is necessary for
the provision of smart services, such as health care and behavior change support in “real …

Several techniques for human activity recognition (HAR) in a smart indoor environment have
been developed and improved along with the rapid advancement of sensor technologies …

Applying deep learning to IoT data classification would yield deeper and more useful
insights. IoT field is very wide and has several applications. In this paper we focus on smart …

While the sensor-based recognition of Activities of Daily Living (ADLs) is a well-established
research area, few high-quality labeled datasets are available to compare the results of …

This paper presents an overview of state of art of multi resident activity recognition in smart
home environment. Generally wearable sensors as well as bespoke sensors are used for …

Due to the aging population, home care for the elderly has become very important.
Currently, there are many studies focusing on the deployment of various sensors in the …

Abstract Human Activity Recognition (HAR) integrates ambient assisted living (AAL), leading
to smart home automation for monitoring activities, healthcare, fall detection, etc. Various …