1 / 14

REU 2007

REU 2007. 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.

teneil
Download Presentation

REU 2007

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. REU 2007 Research Experiences for Undergraduates in Information Processing and Decision Making for Intelligent and Secure Environments Computer Science and Engineering DepartmentThe University of Texas at Arlington

  2. Computer Science and Engineering DepartmentThe University of Texas at Arlington Intelligent Environments: MavHome - An Intelligent Home • Detailed MavHome description: • http://ranger.uta.edu/smarthome

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

  4. Smart House Automated blinds Door/lock controllers, Surveillance system Face recognition, automated door entry Climate control Intelligent appliances Remote site monitoring and control Assistance for disabilities Robot vacuum cleaner Lighting control Robot lawnmower Intelligent Entertainment Smart sprinklers

  5. 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

  6. 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

  7. MavHome Architecture Machine Learning

  8. 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

  9. 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

  10. MavLab Goal: minimize interactions Powerline control of devices Prediction and data mining Decision making Robotics

  11. MavPad • UTA apartment housing undergraduate student • PDA interface • Control of heat/AC, water, blinds, vents, all electrical devices

  12. Example System: MavHome

  13. Example System: MavHome • Example task: getting up in the morning and taking a shower.

  14. Example System: MavHome • Home learns to automate light activations such as to minimize energy usage without increasing the number of inhabitant interactions

More Related