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Context-aware monitoring is an emerging technology that provides real-time personalised health-care services and a rich area of big data application. In this paper, we propose a knowledge discovery-based approach that allows the context-aware system to adapt its behaviour in runtime by analysing large amounts of data generated in ambient assisted living (AAL) systems and stored in cloud repositories...
The past few years have seen an exponential growth in data collection capabilities. Unfortunately, the ability to process this vast amount of data has not kept pace with this growth. Taking full advantage of these increased capabilities requires scalable, computationally efficient algorithms to timely and robustly extract actionable information from the very large data sets generated by the sensors...
Context data-driven approach refers to the process of collecting and storing context data from a wide range of context sources as sensors and Web services. This approach differs from existing context-aware applications, where context models and applications are closely related and ignore how the context is derived from sources and interpreted. In this paper, we propose a context data model based on...
In services using lifelog collected continuously and over a long period of time, disclosure control is essential in order to deal with the privacy because this lifelog includes confidential information which users are unwilling to disclose freely. This paper proposes an ontology model for disclosure control needed to handle each user's lifelog. The user is able to easily set disclosure rules on his/her...
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