Context-aware systems architecture (CaSA)

Context-aware systems are becoming increasingly mainstream as more and more technology allows real-time collection of daily life data and it is more and more affordable to provide useful services to citizens in various situations of need. However, developers in this field are not well supported. Naturally we have inherited a number of methods and tools from past software engineering efforts to create previous computing systems. However the most recent generation of systems dominated by sensing supported context-awareness integrating a variety of data sources and with a higher expectation of personalized services delivered at the right time, place and in the right form, are not well supported. Developers need more guidance and support to pinpoint those valuable contexts and to work out ways of detecting them and activating the right services associated with these contexts. Our community has reported on various systems they created however not much is emerging in a way of a methodology, a standard, a transferable body of advice and guidance which can help teams next time they need to develop a new system. In this article we explain a couple of complementary methodologies which we have tried and tested through development of different context-aware projects. We argue these are of practical usefulness and provide an initial valid point of discussion for our community to create evolved versions of these which can be tested more widely to identify good practice in the area

Personalised privacy in pervasive and ubiquitous systems

Our world is edging closer to the realisation of pervasive systems and their integration in our everyday life. While pervasive systems are capable of offering many benefits for everyone, the amount and quality of personal information that becomes available raise concerns about maintaining user privacy and create a real need to reform existing privacy practices and provide appropriate safeguards for the user of pervasive environments. This thesis presents the PERSOnalised Negotiation, Identity Selection and Management (PersoNISM) system; a comprehensive approach to privacy protection in pervasive environments using context aware dynamic personalisation and behaviour learning. The aim of the PersoNISM system is twofold: to provide the user with a comprehensive set of privacy protecting tools and to help them make the best use of these tools according to their privacy needs. The PersoNISM system allows users to: a) configure the terms and conditions of data disclosure through the process of privacy policy negotiation, which addresses the current “take it or leave it” approach; b) use multiple identities to interact with pervasive services to avoid the accumulation of vast amounts of personal information in a single user profile; and c) selectively disclose information based on the type of information, who requests it, under what context, for what purpose and how the information will be treated. The PersoNISM system learns user privacy preferences by monitoring the behaviour of the user and uses them to personalise and/or automate the decision making processes in order to unburden the user from manually controlling these complex mechanisms. The PersoNISM system has been designed, implemented, demonstrated and evaluated during three EU funded projects