Graham Thomson

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Automatically determining the situation of an ad-hoc group of people and devices within a smart environment is a significant challenge in pervasive computing systems. Current approaches often rely on an environment expert to correlate the situations that occur with the available sensor data, while other machine learning based approaches require long(More)
Automatically determining the situation of an ad-hoc group of people and devices within a smart environment is a significant challenge in pervasive computing systems. Current approaches often rely on an environment expert to correlate the situations that occur with the available sensor data, while other machine learning based approaches require long(More)
With computing and communication capabilities now embedded in most physical objects of the surrounding environment and most users carrying wireless computing devices, the Ambient Intelligence (AmI) / pervasive computing vision [28] pioneered by Mark Weiser [32] is becoming a reality. Devices carried by nomadic users can seamlessly network with a variety of(More)
As a variety of pervasive environments emerge, context-aware applications shall have to interact well with each of them. In this position paper, we propose extensions to the Strathclyde Context Infrastructure that gives context-aware applications the potential to adapt to such environments transparently. We present a vision of a context discovery technique(More)