Smart Data Collection and Management in Heterogeneous Ubiquitous Healthcare

The increasing availability of network connection and the progress in information technology and in hardware miniaturization techniques, are determining new computing scenarios, where software applications are able to "configure themselves" based on information coming from heterogeneous sources (sensors, RFID, GPS, databases, user input, etc.) which form the so called "context". In other terms, such applications are based on the representation and codification of different kinds of data, such as biomedical parameters, environmental data, device location, user preferences, resource availability, every time, from every location and through different modalities (pervasiveness), and on the provision of services and contents adapted to current context (context-awareness). Such computing scenarios find application in a large number of real-life domains, as environment monitoring, supply-chain management and so on. Health-care is perhaps one of the most relevant and promising. Indeed, the perspectives opened by such technologies are wide and variegate: they range from the home-care of mobility-impaired people to the harmonization and presentation to hospital workers of information gathered from distributed heterogeneous sources. The implementation of context-aware systems is based on two distinct but strongly interlaced tasks: 1) monitoring and collection of sensorial data, with the related issues concerning data transmission, costs, enabling technologies as well as the heterogeneity and the number of data to be collected 2) processing and integration of data with available context information in order to activate decision processes which are in many cases not trivial. Key points are the selection of the enabling technologies for the collection, transmission and smart management of data gathered from heterogeneous sources, and the design of a system architecture having the following characteristics: a. simple to use; b. low-cost and low-power consumption in order to make possible the implementation of systems with a high number of nodes; c. interoperable with any type of sensors; d. customizable to different kinds of application domains with a limited effort; e. scalable with the number of nodes;