Context-Aware Smart Spaces:
Ubiquitous computing offers the vision of a physical environment that is fundamentally more responsive to people. Users will be able to benefit from the “smartness” of rooms and public spaces to seamlessly interact with a wide variety of internetworked wireless and wired devices, e.g. printers, monitors, speakers, wearable computers, appliances, kiosks, toys, sensors, other wireless personal digital assistants and other video-enabled mobile phones. Emerging technologies such as wireless pico-cell Bluetooth networks, wireless Ethernet, third generation high speed cellular systems, low power high speed microprocessors, and matchbox-sized gigabyte disks are already hastening the arrival of a world in which smart spaces are truly pervasive.
Automated selection of the UI eases the user’s interaction with a pervasive environment, in comparison to manual selection, which is cumbersome, and directional remote control, e.g. pointing and clicking, which is insufficient to resolve the active device ambiguity when a group of devices is closely spaced, as in a home entertainment system. Our goal is to anticipate the next user interface desired by the user based on each user’s history of remote control accesses.
We are currently collecting traces of user remote control behavior while utilizing a wireless PDA. We are subjecting these traces to a variety of various A.I./machine learning prediction algorithms, including first and second order Markov prediction as well as naïve Bayesian prediction. We have been able to obtain accuracies of prediction thus far of 75-90%, depending upon the algorithm and the degree of training.