A New Approach to Behavioral Reasoning in Smart Homes using DVSM Algorithm

Smart Homes (SH) have gradually visible as realistic assistive environments capable of providing assistive living for the elderly and the disabled people.The machine learning and the sensing technology are implemented in the smart homes. The technologies are designed to recognize and track normal activities of people in routine life. The labeled training data are available for activities that are preselected. A computerized access is used to Behavior tracking that analyze frequent activities. We can then track the reliability of continuous behavioral activities to observe the functional health and to make changes in an individual’s sequence and resident’s lifestyle. In this work, we discuss about the Behavior mining and tracking approach, and validate our HMM and the DVSM algorithms based on the data collected in physical smart environments.