By the development of image processing systems, human behavior prediction has been
grown for research. Many research outcomes are previously available to recognize human …

Wearable sensors are widely used in medical applications and human–computer interaction
because of their portability and powerful privacy. Human activity identification based on …

Automated behaviors in an environment can be implemented based on aggregation of
individual user routines. For example, mobile devices used by users in the environment can …

Windowing is an established technique employed within dense sensing environments to
extract relevant features from sensor data streams. Among the established approaches of …

Smart homes have been recently important sources for providing Activity of Daily Living
(ADL) data about their residents. ADL data can be a great asset while analyzing residents' …

There has been significant recent interest in sensing systems and 'smart environments', with
a number of longitudinal studies in this area. Typically the goal of these studies is to develop …

In active and assisted living environments, a major service that can be provided is the
automated assessment of elderly people's well-being. Therefore, activity recognition is …

Activity prediction aims to predict what activities will occur in the future. In smart homes, to
facilitate the daily living of the residents, automated or assistive services are provided. To …

Developing tools to understand and visualize lifestyle is of high interest when addressing
the improvement of habits and well-being of people. Routine, defined as the usual things …

One of the major problems faced by automated human activity recognition systems is the
scalability. Since the probabilistic models employed in activity recognition require labeled …