Context-Based Adaptation of Mobile Phones Ussing Near-Field Communication

Abstract

Smart environments that can adapt based on the current context are extremely useful for automating even simple, mundane tasks. The key components of such an environment are sources that can extract the raw context, a synthesizer that can draw inferences by aggregating the context from different sources, and a set of policies that drive the adaptation. In this paper, we describe a context-based adaptation system to alleviate the distraction caused by one of the most ubiquitous devices of modern day-the mobile phone. Our system makes use of sources, such as RFID devices, that employ near-field communication technology to extract raw context. We describe how we adapt the roles of these devices to extract both environmental and personal context. To reduce the distraction caused by mobile phones, we have developed a policy-based mechanism to enable context-based adaptation of these devices. We have implemented a prototype of our system and conducted some usage studies. We describe the details of our implementation and present the lessons learned from the usability experiments