Abstract Automatic human Activity Recognition (AR) is an important process for the provision
of context-aware services in smart spaces such as voice-controlled smart homes. This paper …

Accurately recognizing human activities from sensor data recorded in a smart home setting
is a challenging task. Typically, probabilistic models such as the hidden Markov model …

Activities of Daily Livings (ADLs) refer to the activities that are carried out by an individual for
everyday living. Recognition of ADLs is key element for building intelligent and pervasive …

Activities of daily living are good indicators of elderly health status, and activity recognition in
smart environments is a well-known problem that has been previously addressed by several …

This paper presents the application of Markov Logic Networks (MLN) for the the recognition
of Activities of Daily Living (ADL) in a smart home. We describe a procedure that uses raw …

Smart environments with ubiquitous sensing technologies are a promising perspective for
reliable and continuous healthcare systems with reduced costs. A primary challenge for …

Human activity recognition (HAR) is fundamental to many services in smart buildings.
However, providing sufficiently robust activity recognition systems that could be confidently …

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

Increasing attention to the research on activity monitoring in smart homes has motivated the
employment of ambient intelligence to reduce the deployment cost and solve the privacy …