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Intelligent Environments. Computer Science and Engineering University of Texas at Arlington. Course Overview. Course website http://ranger.uta.edu/~holder/courses/cse6362.html Major topics Sensors, Networks, Database Prediction, Decision-Making Robotics Privacy and Security.
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Intelligent Environments Computer Science and Engineering University of Texas at Arlington Intelligent Environments
Course Overview • Course website • http://ranger.uta.edu/~holder/courses/cse6362.html • Major topics • Sensors, Networks, Database • Prediction, Decision-Making • Robotics • Privacy and Security Intelligent Environments
Course Overview • Readings, lectures, quizzes • Homeworks • HW1: Sensors • HW2: Networks • HW3: Database • HW4: Prediction and Decision-Making Intelligent Environments
Course Overview • Presentation topics • Architectural design • Human-computer interfaces • Visualization • Smart materials • Energy efficiency • … Intelligent Environments
Course Overview • Project • Simulated intelligent environment • Sensors • Network • Database • Prediction and decision-making • Scenario-based design • Project demonstration Intelligent Environments
Course Overview • Invited Speakers • … Intelligent Environments
Intelligent Environments Introduction Intelligent Environments
Definitions • Intelligent • Able to acquire and apply knowledge • Knowledge is more than data • Environment • Surroundings • Intelligent Environment • An environment able to acquire and apply knowledge about you and your surroundings in order to improve your experience. Intelligent Environments
Definitions • “Improve your experience” • Comfort • Security • Efficiency • Productivity Intelligent Environments
IE Scenarios • Your house learns your living patterns in order to optimize energy efficiency. • Turn down the HVAC when you are gone • Your house learns that you like to sleep later on Saturdays. • Postpone morning events (e.g., coffee-maker, alarm, shades, …) • Your house adapts to the entertainment center settings of each inhabitant • Volume, favorite channels Intelligent Environments
IE Scenarios (cont.) • Your car collects information about its environment as you drive • Theatre locations, times, ticket availability • Restaurant locations, cuisine, mean wait time • Gas stations, facilities • Emergency care, closest, facilities • Recommendations based on learned preferences and destination prediction Intelligent Environments
More IE Scenarios • ??? Intelligent Environments
Intelligent Environments Projects Intelligent Environments
IE Projects: Academic • UTA MavHome Smart Home • Georgia Tech Aware Home • MIT Intelligent Room • MIT House_n • Stanford Interactive Workspaces • UC Boulder Adaptive House Intelligent Environments
IE Projects: Commercial • General Electric Smart Home • Microsoft Easy Living • Philips Vision of the Future Intelligent Environments
Georgia Tech Aware Home • Perceive and assist occupants • Aging in Place (crisis support) • Ubiquitous sensing • Scene understanding, object recognition • Multi-camera, multi-person tracking • Context-based activity • Smart floor • www.cc.gatech.edu/fce/ahri Intelligent Environments
MIT Intelligent Room • Support natural interaction with room • Speech • Gesture • Movement • Context • Numerous projects • www.ai.mit.edu/projects/iroom • Supported by MIT Project Oxygen (pervasive computing) • oxygen.ai.mit.edu Intelligent Environments
MIT house_n • MIT Department of Architecture • Dynamic, evolving places that respond to the complexities of life • New technologies • New materials • New design strategies • architecture.mit.edu/house_n Intelligent Environments
Stanford Interactive Workspaces • Large wall and tabletop interactive displays • Scientific visualization • Mobile computing devices • Computer-supported cooperative work • Distributed system architectures • graphics.stanford.edu/projects/iwork Intelligent Environments
UC Boulder Adaptive House • Infer patterns and predict actions • HVAC, water heater, lighting • Goals • Reduce occupant manual control • Energy efficiency • Nice simulation • www.cs.colorado.edu/~mozer/house Intelligent Environments
General Electric Smart Home • Appliance control • Climate control • Energy management • Lighting control • Security • Consumer Electronics Bus (CEBus) • www.ge-smart.com Intelligent Environments
Microsoft Easy Living • Camera-based person detection and tracking • Geometric world modeling for context • Sensor fusion • Authentication • Distributed systems • Ubiquitous computing • research.microsoft.com/easyliving Intelligent Environments
Philips Vision of the Future • Less obtrusive technology • Heart controller • Lots of gadgets • Interactive wallpaper • Control wands • Intelligent garbage can • www.design.philips.com/vof Intelligent Environments
UTA MavHome Smart Home • Focus on entire home as a rational agent • Goals • Maximize comfort and productivity of inhabitants • Minimize cost • Ensure security • Reasoning and adaptation • ranger.uta.edu/smarthome Intelligent Environments
UTA MavHome Smart Home Intelligent Environments
UTA MavHome Projects • CSE Projects • MavHome Agent Design (Cook, Holder, Huber, Kamangar) • Predicting inhabitant and house behaviors (Cook, Holder) • Robot assistance (Huber, Cook) • Web monitoring and control (Kamangar) • Distributed sensor fusion (Kamangar) • Database monitoring (Chakravarthy) • Multimedia traffic for entertainment and security (Yerraballi) • Intelligent routing, mobility prediction (Das) • Cross-Disciplinary Projects • Smart materials and structures (Civil Engineering) • Nano structures (Electrical Engineering) • Device communication (Telcordia Technologies) Intelligent Environments
MavHome Sponsors • National Science Foundation ($1.2M) • UTA to fund house • Nortel, $100K to Das for research • Friendly Robotics, robot donation • Potential • NIH (assistance for people with disabilities) • DARPA (military applications) • Ericsson, Motorola, Nokia, Dallas Semiconductor Intelligent Environments
Proposed MavHome Location • Southeast corner of UTA Blvd and Davis Nedderman Hall Intelligent Environments
MavHome FloorPlan (1st floor) Intelligent Environments
MavHome FloorPlan (2nd floor) Intelligent Environments
Intelligent Environments Challenges Intelligent Environments
IE Challenges • Sensors • Type • Number • Interference • Autonomous • Active vs. Passive • Communication • Interface Intelligent Environments
IE Challenges • Networking • Wired vs. Wireless • Protocol(s) • Bandwidth • Organization Intelligent Environments
IE Challenges • Data storage • Size • Query rate • Active vs. Passive • Decision-making • Communication Intelligent Environments
IE Challenges • Prediction and Decision-Making • Dynamic, temporal patterns • Data relevance • Sensor fusion • Real-time • Autonomy Intelligent Environments
IE Challenges • Robotics • Mechanical capabilities • Learning • Safety • Privacy and Security • Unwanted surveillance • “Break-ins” Intelligent Environments
IE Challenges • System architecture • Agent-based vs. monolithic • Hierarchical vs. flat • Distributed vs. centralized control • Systems integration • Plug-n-play everything • Existing appliances Intelligent Environments
IE Design: Smart Home • Physical home design • New vs. retrofit • Home architecture • Materials • Sensors, Networking, Database • Prediction and Decision-making • System architecture Intelligent Environments
My Smart Home ? Intelligent Environments