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In this paper, the trend as an important component in activities of daily living is modelled and integrated to a single-occupant occupancy simulator. Therefore, in the occupancy signal generated by the simulator, both seasonality and trend are included in occupant's movements. As the result of trends integrated to the simulator, occupancy signals with different types of trends such as increasing,...
In this paper, occupancy pattern extraction and prediction in an intelligent inhabited environment is addressed. The results of this research will help elderly people to live independently in their own home longer and help them in case of an emergency. Using a wireless sensor network system, daily behavioral patterns of the occupant are extracted. This information is then used to build a behavioral...
The application of wireless localizing agents in the occupancy detection of a single-occupant ambient intelligent environment in the presence of visitors is addressed in this paper. A wireless sensor network constructed from sensory agents of PIR motion detection sensors and door contact sensors is employed to collect the occupancy data from different areas in the ambient intelligent environment....
In this paper, the simulation of an occupant's behaviour in a single-occupant ambient intelligent environment is addressed. The algorithm of the simulator is designed flexible enough to accept different environmental profiles including the number of areas and the connections between them along with different occupant's profiles including expected daily occupancy pattern of him/her and the uncertainty...
In this paper, the prediction of the occupancy of different areas in a single-occupant intelligent inhabited environment is addressed It is aimed to deliver a well-being monitoring and assistive environment to support elderly to live independently. A wireless sensor network of motion detection sensors is constructed to collect the required occupancy data. Individual sensory data are combined to form...
In this paper, a review of prediction techniques suitable for ambient intelligence environments is presented. Prediction challenges in sensor networks are considered in two phases including pattern extraction and rule matching. The prediction techniques reviewed in this paper come from two main research areas, namely, data mining and soft computing techniques. Moreover, a statistical modelling technique...
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