Um ambiente de contexto personalizado e orientado a tarefas na arquitetura ClinicSpace

• Ano de defesa: 2009
• Autor(a) principal: Rizzetti, Tiago Antonio
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; BR; Ciência da Computação; UFSM; Programa de Pós-Graduação em Informática
• Palavras-chave em Português: Computação pervasiva; Computação ubíqua; Computação sensível ao contexto; Middleware; Computação orientada a tarefas; Tarefas clínicas; Personalização de contexto; Entrada implícita de dados; Pervasive computing; Ubiquitous computing; Context-sensitive computing; Task-based computing; Clinical tasks; Context customization; Implicit data entry; CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: http://repositorio.ufsm.br/handle/1/5352

The project ClinicSpace aims to fill gaps in current clinical systems, regarding to the characteristics of pervasive computing tasks and clinical activities support to the user (physician). The architecture of the model ClinicSpace, built from the perspective given by the activity theory, it is composed of several modules that interconnected offer the features needed in a system geared to clinical pervasive end-user. One of these modules is the treatment of the clinical tasks. This work holds a discussion on the present requirements for the treatment of the clinical tasks, defining an architecture to link them to the tasks of the user, allowing context customization and automatic entry of data. The customization is achieved through the use of Programmable Elements of Context, which are represented by actuators, physical or logical, responsible for providing the system capacity of automatic executions, based on the parameters specified by the user. Yet the automatic data comes from the implicit way of obtaining these, the information used by applications that the user performs in the course of their duties. For this, an architecture was set up to support the customization and the semantic specification of data used. Building such features extended the pervasive middleware EXEHDA, modifying the already existing services and adding new ones. The main contribution of this work is the interconnection between the components that make up the architecture, building a unique view of the context of a task from the perspective of the necessary data for it and the ability to be customized by the user. Thus, it reduces the need for explicit data entry, and it contributes to the reducing rejections of its adoption of clinical systems in highly dynamic environments such as hospitals.