Caroline S. Langensiepen

Learn More
In this paper we have described a solution for supporting independent living of the elderly by means of equipping their home with a simple sensor network to monitor their behaviour. Standard home automation sensors including movement sensors and door entry point sensors are used. By monitoring the sensor data, important information regarding any anomalous(More)
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.(More)
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(More)
In this paper, the application of soft computing techniques in prediction of an occupant's behaviour in an inhabited intelligent environment is addressed. In this research, daily activities of elderly people who live in their own homes suffering from dementia are studied. Occupancy sensors are used to extract the movement patterns of the occupant. The(More)
Pattern analysis and prediction of sensory data is becoming an increasing scientific challenge and a massive economical interest supports the need for better pattern mining techniques. The aim of this paper is to investigate efficient mining of useful information from a sensor network representing an ambient intelligence environment. The goal is to extract(More)
Identifying abnormal behaviour is an important factor in activity recognition. The aim of this paper is to design a system able to detect the abnormal behaviours of daily activity living in an intelligent environment. We approach this by applying dissimilarity (distance) measures on data collected from a single inhabitant environment. The data are acquired(More)