Ehsan Ullah Warriach

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Pervasive computing environments such as our future homes are the prototypical example of a dynamic, complex system where Service-Oriented Computing techniques will play an important role. A home equipped with heterogeneous devices, whose services and location constantly change, needs to behave as a coherent system supporting its inhabitants. In this paper,(More)
Domotics, concerned with the realization of intelligent home environments, is a novel field which can highly benefit from solutions inspired by service-oriented principles to enhance the convenience and security of modern home residents. In this work, we present an architecture for a smart home, starting from the lower device interconnectivity level up to(More)
Wireless Sensor Network (WSN) deployment experiences show that collected data is prone to be faulty. Faults are due to internal and external influences, such as calibration, low battery, environmental interference and sensor aging. However, only few solutions exist to deal with faulty sensory data in WSN. We develop a statistical approach to detect and(More)
Wireless Sensor Network (WSN) deployment experiences show that data collected is prone to be imprecise and faulty due to internal and external influences, such as battery drain, environmental interference, sensor aging. An early detection of such faults is necessary for the effective operation of the sensor network. In this preliminary work, we propose a(More)
The future home will be pervaded by mobile and stationary devices which need to dynamically connect and coordinate in order to seamlessly help people in accomplishing their tasks. However, for this vision to become a reality , it is important for researcher and developer to build applications that constantly adapt and integrate heterogeneous devices(More)
Wireless Sensor Network (WSN) deployment experiences show that collected data is prone to be faulty. Faults are due to internal and external influences, such as calibration, low battery, environmental interference and sensor aging. However, only few solutions exist to deal with faulty sensory data in WSN. We develop a statistical approach to detect and(More)
This article describes the implementation of four different machine learning techniques for vehicle classification in a dual ultrasonic/passive infrared traffic flow sensors. Using k-NN, Naive Bayes, SVM and KNN-SVM algorithms, we show that KNN-SVM significantly outperforms other algorithms in terms of classification accuracy. We also show that some of(More)