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Privacy is an important aspect of pervasive and ubiquitous computing systems, and, in particular, pervasive healthcare. With reference to previous approaches on developing privacy sensitive pervasive healthcare applications, we detail a framework for the design of such systems that aims to minimise the impact of privacy on such systems. In reviewing previous approaches, we extract and combine common...
This paper examines the recovery of user context in indoor environmnents with existing wireless infrastructures to enable assistive systems. We present a novel approach to the extraction of user context, casting the problem of context recovery as an unsupervised, clustering problem. A well known density-based clustering technique, DBSCAN, is adapted to recover user context that includes user motion...
In implementing privacy protection in surveillance systems, designers must maximize privacy while retaining the system's purpose. One way to achieve this is to combine data-hiding techniques with context-aware policies governing access to securely collected and stored data.
In this paper we present preliminary work implementing dynamic privacy in public surveillance. The aim is to maximise the privacy of those under surveillance, while giving an observer access to sufficient information to perform their duties. As these aspects are in conflict, a dynamic approach to privacy is required to balance the systempsilas purpose with the systempsilas privacy. Dynamic privacy...
To tackle the problem of increasing numbers of state transition parameters when the number of sensors increases, we present a probabilistic model together with several parsinomious representations for sensor fusion. These include context specific independence (CSI), mixtures of smaller multinomials and softmax function representations to compactly represent the state transitions of a large number...
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