REU 2007 Computer Science and Engineering Department The University of Texas at Arlington Research...

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Motivations  Unified project incorporating varied AI techniques, cross disciplinary with mobile computing, databases, multimedia, and others  High visibility  Possible commercial implications

Transcript of REU 2007 Computer Science and Engineering Department The University of Texas at Arlington Research...

REU 2007 Computer Science and Engineering Department The University of Texas at Arlington Research Experiences for Undergraduates in Information Processing and Decision Making for Intelligent and Secure Environments Computer Science and Engineering Department The University of Texas at Arlington Intelligent Environments: MavHome - An Intelligent Home Detailed MavHome description: Motivations Unified project incorporating varied AI techniques, cross disciplinary with mobile computing, databases, multimedia, and others High visibility Possible commercial implications Smart House Face recognition, automated door entry Smart sprinklers Lighting control Door/lock controllers, Surveillance system Robot vacuum cleaner Robot lawnmower Intelligent appliances Climate control Intelligent Entertainment Automated blinds Remote site monitoring and control Assistance for disabilities UTA MavHome Capabilities UTA Project Unique Focus on entire home House perceives and acts Sensors Controllers for devices Connections to the mobile user and Internet House optimizes goal function Maximize inhabitant comfort Minimize cost Maximize user productivity Maximize security Smart Home - An Adaptive Environment Smart Home is a home environment that adapts to the inhabitants It has to sense the state of the home and the presence of people It has to predict their behavior It has to make decisions in order to automate the home MavHome Architecture Machine Learning UTA MavHome Components Decision Layer Hierarchical Reinforcement Learning Information Layer Reactive / Proactive Information Repository Predicting inhabitant and house behaviors Mobility prediction Communication Layer Intelligent routing Supporting location-aware / context-aware services Specialized Agents Smart distributed sensor network Personal service robots Multimedia agent Service Robots and Intelligent Environments Assistance for Persons with Disabilities Communication devices and technologies Intelligent assistive devices IT for improved care Information Technologies for Healthcare and Aging Automatic health monitoring Intelligent environments IT to improve uniform communication needs MavLab Goal: minimize interactions Powerline control of devices Prediction and data mining Decision making Robotics MavPad UTA apartment housing undergraduate student PDA interface Control of heat/AC, water, blinds, vents, all electrical devices Example System: MavHome Example task: getting up in the morning and taking a shower. Example System: MavHome Home learns to automate light activations such as to minimize energy usage without increasing the number of inhabitant interactions