Intention as a Context: An Activity Intention Model for Adaptable Development of Applications in the Internet of Things

Abstract

End-users, such as aging people, look for dynamic applications to help them in their daily activities while usually assisted by domain experts (e.g., physicians) in performing these activities. Nowadays, the Internet of Things (IoT) augments applications with a changing context based on the activities, environments, and services. Unfortunately, most IoT application development tools are restricted to specific scenarios or involve technical challenges. We propose an activity intention model for quick application development, targeting domain experts who are not traditional software developers. Our model is based on the ContextAA micro context-awareness approach with autonomic computing-based components providing pervasive adaptations. Unlike other Internet of Things application definitions, our model promotes elicitation of the activity semantics and provides mechanisms to compute the semantics. We then generate intention as a context (IaaC), which contains a self-described activity intention context with compiled knowledge ready to be assessed in pervasive smart environments for augmented adaptations. Experimental results show a potential resource optimization for dynamic Internet of Things applications in smart homes and smart cities.