A General Context-Aware Framework for Improved Human-System Interactions

42 AI MAGAZINE Context awareness has recently become an important research topic. This is partly driven by rapid growth in the “Internet of Things,” which the Gartner Group predicts will grow to more than 30 billion connected devices, sensors, and computers by 2020 (Middleton, Kjeldsen, and Sutton 2013). Consequently, the types of environments, tasks, and situations in which users, machines, and intelligent services will interact are increasingly diverse. Users’ preferences and their decisions may change depending on the situation. Accordingly, systems should be able to provide the right information, at the right time, in the most appropriate format for that particular user and situation. To effectively collaborate, both humans and automation (whether robots, smart homes, or personal software assistants) need access to a common representation of potentially relevant situational information, or context. Monitoring and mining humanmachine interactions and reasoning over this data enables new types of adaptive and personalized applications. But what exactly is context, how is it different from other types