Identificação contextualizada de objetos e pessoas na arquitetura ClinicSpace

Abstract

The health systems of the future point to the use of pervasive computing, which aims to help users in their daily activities. Accordingly, we seek to make the systems more oriented to end-user, reducing the distance between how the user performs activities and modeling these in information to a Health s system, providing to the doctor services that meet the requirements as proactivity and the context which his activities are performed. To meet these requirements, the project ClinicSpace (which aims to assist clinicians in their clinical activities) prototyped a software architecture that is developed from the point of view of the user (doctor), oriented to clinical activities, context-aware, based on mobile and pervasive technologies, using techniques of end-user s programming. Identify the elements that act / participate in the context of clinical activities in an automated way and adapt the information from the identification process are goals of this dissertation. Thus was created a model of contextualized identification that guided the development of an architecture, resulting in the identification service to ClinicSpace. Through an XML structure and the use of tags QRCodes was possible to identify and distinguish the elements known and not known for the architecture ClinicSpace and, with the adaptation module, contextualize this information. Impact tests were performed to validate the solution and allow to improvement and refinement it to use in ClinicSpace.