Modern home theater systems require users to control various devices simultaneously including a TV, audio equipment, DVD and video players, and a receiver. To perform the requested user functions in this situation, the user is required to know the functions and positions of the buttons on several remote controls. Users will become more confused if a ubiquitous home environment, which contains many mobile and stationary control devices, is realized. Therefore, the user interface should be adaptable for requested user functions and to fit a specific control device. This paper presents a context-Adaptive user interface for the control of devices in ubiquitous home environment. First, we modeled the ubiquitous home environment in order to implement the context-Adaptive user interface. We used a Bayesian network to predict the necessary devices in each situation and used a behavior network to select the functions that constitute an adaptive user interface in several conditions. The selected functions were used to generate an adaptive interface for each controller using a presentation template. In this paper, we implemented a ubiquitous home environment and generated a controller usage log for this environment. We confirmed that the Bayesian network effectively predicted the user requirements by evaluating the inferred results of the necessary devices based on several scenarios. Finally, we compared the adaptive user interface with the fixed user interface by surveying fourteen subjects. We confirmed that the generated adaptive user interface was more comfortable for use with typical tasks than was the fixed user interface.
Bibliographical noteFunding Information:
The authors would like to thank Dr. Han-Saem Park for preparing for this manuscripts. This research is supported by Ministry of Culture, Sports and Tourism (MCST) and Korea Creative Content Agency (KOCCA) in the Culture Technology (CT) Research & Development Program, and by Korea Communications Commission (KCC) as a project, ”Development of UX based Smart TV Environmental Status Recognition Technology.”
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Artificial Intelligence