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WSU CSE 6362 - Lecture Notes

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Slide 1MavHome Current and Future DirectionsContentsPrincipal Investigators, Students, and Current ResearchPrediction GroupMobility Prediction GroupLearning/Decision Making GroupDatabase GroupSensors GroupRobotics GroupMultimedia GroupModeling & Simulation GroupAdditional ResearchersTCU MavHome ResearchQuestions?Future ProjectsSensorsSmart KitchenSecurityEntertainmentMedical/Health MonitoringWeb TechnologiesVision Systems / Inhabitant LocalizationHuman-Computer InterfaceRoboticsImproving Current Software & ResearchMilestones in 2003Slide 28MavHome / AI Lab TechnologyX10 Awesome SystemX10 Good & BadResiSimSlide 33Slide 34ResiSim LauncherResiSim ServerResiSim ClientMavHome Agent & PredictionSlide 39Automated Mini-blindsMavHome / AI Lab ArchitectureAgent ArchitectureAgent HierarchyWork in ProgressSlide 45MavHome ConstructionFactsBuilder & ArchitectSiteNorth ViewNorth ElevationEast SideEast ElevationLower FloorUpper FloorScheduleReviewSlide 58Slide 5901/13/19 ©2003 G. Michael Youngblood, [email protected] and Future DirectionsG. Michael YoungbloodChief ScientistThe MavHome ProjectThe University of Texas at Arlington01/13/19 ©2003 G. Michael Youngblood, [email protected]Principal Investigators, Students, andCurrent ResearchFuture ProjectsMavHome/AI Lab TechnologyMavHome/AI Lab ArchitectureMavHome Construction01/13/19 ©2003 G. Michael Youngblood, [email protected] Investigators,Students, andCurrent ResearchAI Lab250NH01/13/19 ©2003 G. Michael Youngblood, [email protected] GroupDiane J. Cook, Ph.D.MavHome Lead Principal InvestigatorThis group is engaged in work to learn inhabitant patterns and predict the next appropriate action to take, who the inhabitant is, or what activity the inhabitant is engaged in.Ed Heierman PhD ED/IPAM (Data mining techniques)Sira P. Rao MS TMM (Markov Model based)Ritesh Mehta MS Subdue-based Inhabitant ClassificationAndrey Litvin BS MetaPredictor (Predition aggregator)Karthik GopalratnumBS Active LeZi-Update (Compression algorithm approach)01/13/19 ©2003 G. Michael Youngblood, [email protected] Prediction GroupSajal K. Das, Ph.D.This group is engaged in work to determine the next location an inhabitant will move to next and how to route sensor and other network based message traffic appropriately and efficiently.Abhishek Roy PhD LeZi-UpdateSoumya Das Bhaumik BS LeZi-Update InterfacingWook Choi MS Routing in sensor and ad hoc networks01/13/19 ©2003 G. Michael Youngblood, [email protected]/Decision Making GroupManfred Huber, Ph.D.Diane J. Cook, Ph.D.Larry Holder, Ph.D.This group is engaged in work to determine the best way to represent state information and to create a hierarchical-based reinforcement learner. Learning with agent-based architectures and association rules is a focus. The issue of how to best represent the inherent spatial-temporal information of MavHome interaction information is also a major area of research.Michael YoungbloodPhD MavHome Agent Architecture, hierarchical reinforcement learningMehran Asadi MS Learning state abstractions for hierarchical learningSandeep Goel MS Learning action hierarchiesKareemuddin Syed MohammedMS Learning timing events01/13/19 ©2003 G. Michael Youngblood, [email protected] GroupSharma Chakravarthy, Ph.D.This group is engaged in research involving active databases which move learning into the database architecture and stream mining of data going into storage to determine interesting patterns and generate association rules. They are also investigating the area of concept drift.Ambika SrinivasanMS Active Databases / ROI / Temporal ClusteringSatyajeet Sonune MS Active Databases / Stream mining / VisualizationAltaf Giliani MS Active Databases / Stream mining01/13/19 ©2003 G. Michael Youngblood, [email protected] GroupFarhad Kamangar, Ph.D.This group is engaged in vision processing work currently focused on face recognition for inhabitant identification at entry points in the intelligent environments. Work in this area is also focused on inhabitant localization and sensor networks.Ashutosh Agrawal MS Face Recognition01/13/19 ©2003 G. Michael Youngblood, [email protected] GroupManfred Huber, Ph.D.Diane J. Cook, Ph.D.This group is engaged in research on robots for home use. The current focus is using the Sony Aibo robot for navigation to act as a security agent for the MavHome. Other uses for Aibo include bring needed medicine to an inhabitant or acting as a truly mobile communication device or assessment tool (relaying audio, video, and telemetry information to emergency services) for an endangered inhabitant.Yi “Wendy” Wang BS Aibo navigation01/13/19 ©2003 G. Michael Youngblood, [email protected] GroupRamesh Yeraballi, Ph.D.Diane J. Cook, Ph.D.This group is engaged in research with providing multimedia on-demand and learning media preferences. This work also includes some decision making research for the MavHome to best decide what programs to record for later playback based on learned inhabitant information.Jasmin Kanabar MS Video on Demand for a Community of Smart HomesDarin Brezeale PhD Learning preferences and content decision making for audio/video streams01/13/19 ©2003 G. Michael Youngblood, [email protected] & Simulation GroupMichael Youngblood, M.S.This group is engaged in research focused on creating a complete simulation solution for intelligent environments from 3D real-time visual simulation to correct and complete physics and learned-profile math modeling of environmental objects. The final goal is a modeling, building, and client-server comprehensive real-time simulation and playback system that integrates fully with all MavHome components, virtual and real.Michael Youngblood PhD ResiSim – Simulation Engine / Math ModelsMichael Brownlow MS ResiSim – Graphics EngineMichael Garcia BS ResiSim – Network CommunicationsAbhilash Maniam MS ResiSim – Audio EngineAbbasali Ginwala MS ResiSim – Math Model for appliance/object power consumption01/13/19 ©2003 G. Michael Youngblood, [email protected] ResearchersDiane J. Cook, Ph.D.These individuals are engaged in additional MavHome research as listed.Farhan Khawaja BS Automated mini-blinds & learning mini-blind settingsDenis Gjoni BS Automated mini-blindsCourtney Pace BS Voice recognition for MavHomeAbbasali Ginwala MS Appliance/object power consumption and energy consumption characteristics.01/13/19 ©2003 G. Michael

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