Method and Apparatus for Adapting Display to Match User-Specific Information Preferences

Background The human brain is only capable of processing a limited amount of information at one time, but the amount of information that is available to a person in a given situation is infinite. Sifting through all of the information available and pulling out data relevant to the task at hand shifts time and energy away from the primary task. Researchers at UT Austin have developed an adaptive display technology that solves this problem.

Invention Description The invention is an adaptive display technology that seeks to reduce information overload by presenting the information the user desires in the current situation. Machine learning models are used to predict which sources of information the user would like highlighted on a Heads-Up Display (HUD) based on the current situation, leading to faster and higher-quality decision making.

Benefits

Invention presents desired information and filters out distracting information, leading to faster and higher-quality decision making.

Features

Learns and individual user's information preferences across different situations. Is not prescriptive and does not require input from domain experts—user trains the system over the course of normal use.

Market Potential/Applications Applications in which humans operate in information-rich environments - Plant control system - Automobiles, airplanes, and other vehicle - Disaster relief coordinatio - Military command and contro - Personal computer - PDAs

UT Researcher Bradley C. Love, Ph.D., Psychology, The University of Texas at Austin

Type of Offer: Licensing



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