Computer Science and Engineering Department The University of Texas at Arlington MavHome: An Intelligent Home Environment

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

MavHome: An Intelligent Home Environment 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

MavHome Architecture Machine Learning

UTA MavHome Projects • Decision Layer – Hierarchical Reinforcement Learning (Manfred) • Information Layer – Reactive / Proactive Information Repository (Sharma) – Predicting inhabitant and house behaviors (Diane, Larry) – Mobility prediction (Sajal, Diane, Larry) • Communication Layer – Intelligent routing (Sajal) – Supporting location-aware / context-aware services (Sajal) • Specialized Agents – Smart distributed sensor network (Farhad) – Personal service robots (Manfred, Diane) – Multimedia agent (Ramesh)

What Next? •End-of-summer demo •What can you do? –Experiment with sensors and controllers –Modeling –Simulation –CORBA interfaces for sensors and controllers –Send us your ideas!

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