Integrating Human Intention into a Situation Model for Smart Environments
Abstract
Service developers for Smart Environments are increasingly challenged with the issues of information overload and correlation of information from heterogeneous sources. To overcome this barriers different context management technologies have been proposed. Their aim is to support building adaptive and pervasive services for Smart Environments. Actions taken by humans in Smart Environments are heavily influenced by their perception of the situation. Current approaches for context and situation modeling take this hardly into account. They rely on contextual information, based on sensed information of the environment. To integrate human perception of a situation and human intention that is responsible for choosing appropriate tasks of human action, we propose a 3-tier architecture that extends our context model that we have developed in earlier work. Our results were carried out in prototypical services for a Smart Home Environments. We deployed the services in our Smart Home Test Lab.