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This paper presents a distributed multi sensor data processing and fusion system providing sophisticated surveillance capabilities in the urban environment. The system enables visual/non-visual event detection, situation assessment, and semantic event-based reasoning for force protection and civil surveillance applications. The novelties lie in the high level system view approach, not only concentrating on data fusion methodologies per se, but rather on a holistic view of sensor data fusion that provides both lower (sensor) level and higher level (semantic) fusion. At the same time, we concentrate on easy and quick extensibility with new sensors and processing capabilities. The system also makes provisions for visualizing and processing space-time alerts from sensor detections up to high level alerts based on rule-based semantic reasoning over sensor data and fusion events. The proposed architecture has been validated in a number of different synthetic and live urban scenarios.

This paper introduces a novel sensor information fusion system enabling security and surveillance in large scale sensor saturated urban environments. The system is built over state-of-the art sensor networks middleware and provides information fusion at multiple layers. A distinguishing characteristic of the system is that it support seamless integration with semantic web middleware (including ontologies and inference mechanisms), which enable intelligent high-level accurate reasoning. This is a key functionality for efficient surveillance in large scale environment, where manual inspection of individual tracking systems becomes extremely resourceful and overall impractical. A proof-of-concept implementation of the system manifests its benefits and technical challenges, while also outlining lessons learnt.

Clinical guidelines can be represented using models, such as GLIF, specifically designed for healthcare guidelines. This paper demonstrates that they can also be modelled using a mainstream business modelling language such as UML. The paper presents a guideline in GLIF and as UML activity diagrams, and then presents a mapping of GLIF primitives to UML. The potential benefits of using a mainstream modelling language are outlined. These include availability of advanced modelling tools, transfer between modelling tools, and automation via business workflow technology.

Diabetes Mellitus represents a heterogeneous group of metabolic disorders and its complications are associated with increased morbidity and early mortality. The explosive increase of the number of patients with diabetes, and several recommendations from milestone studies such as the United Kingdom Prospective Study (UKPDS), the Diabetes Prevention Program (DPP) and the Finnish Prevention Study place further constraint on an already overstretched service. This paper examines the care flow process in the current diabetes management and explores the potential role of new technologies and methodologies currently available to support the highly complex clinical requirements. The paper proposes a concept of e-clinic as an electronic triage system with integrated healthcare record, embedded with a decision support system to analyse patients' data and provide a continuous monitoring system according to agreed clinical guidelines.