A design approach of proactive HMI based on smart interaction

Abstract

As AI advances, intelligent systems are gaining the ability to collaborate with humans to accomplish everyday tasks proactively. In proactive HMI design, the accuracy of the user intention prediction model in the mechanism becomes the key to affecting the quality of the proactive HMI experience. However, there are three issues that caused the lack of effective ways to improve the prediction accuracy of user prediction models. In this paper, we analyze the Information for improving user prediction accuracy, the Intervention stage, and the required contents for smart interaction. Then, we develop an approach of the proactive HMI based on smart interaction, which is the method that robots learn from the users through interactions. We propose the elements, the framework, and the guidelines. This paper also provides how to use this approach in design case. With this approach, the accuracy of user intention prediction of proactive HMI can be improved and then can be achieved the goal of improving the design effect and the user experience of proactive HMI can be achieved.