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Intelligent Environments 1 Intelligent Environments Conclusions and Future Directions

Intelligent Environments1 Conclusions and Future Directions

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Page 1: Intelligent Environments1 Conclusions and Future Directions

Intelligent Environments 1

Intelligent Environments

Conclusions and Future Directions

Page 2: Intelligent Environments1 Conclusions and Future Directions

Intelligent Environments 2

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.

Page 3: Intelligent Environments1 Conclusions and Future Directions

Intelligent Environments 3

Projects Academic

UTA MavHome Smart Home Georgia Tech Aware Home MIT Intelligent Room MIT House_n Stanford Interactive Workspaces UC Boulder Adaptive House

Commercial IBM Smart Home Microsoft Easy Living

Page 4: Intelligent Environments1 Conclusions and Future Directions

Intelligent Environments 4

Major Topics Sensors Networking Database Prediction Decision Making Robotics Privacy and Security

Page 5: Intelligent Environments1 Conclusions and Future Directions

Intelligent Environments 5

Sensors Issues

Placement Power Interfacing Control

Smart sensors Local memory Local processing Communication

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Intelligent Environments 6

Networking Wired

Phone line Power line New wire

Wireless IEEE 802.11 Bluetooth

Page 7: Intelligent Environments1 Conclusions and Future Directions

Intelligent Environments 7

Networking (cont.) Service Discovery

Jini UPnP

Communication CORBA Java-RMI DCOM

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Intelligent Environments 8

Database Storage requirements

Real-time sensor data User data (esp. multimedia) System information

Prediction and decision-making queries Centralized vs. distributed Sensor databases Active databases

Push paradigm Database triggers

Page 9: Intelligent Environments1 Conclusions and Future Directions

Intelligent Environments 9

Prediction Predicting inhabitant and

environment behavior Sensor fusion and data relevance Concept drift IE-specific prediction

Sequence matching Hidden Markov models Episode discovery

Page 10: Intelligent Environments1 Conclusions and Future Directions

Intelligent Environments 10

Decision Making IE as a rational agent Choose action maximizing

expected utility States of IE Utilities of states Probability action will lead to state

Decision networks

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Intelligent Environments 11

Robotics Robotics for IE

Autonomy Adaptability Human-machine interfacing

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Privacy and Security Physical and data security

Encryption Firewalling Biometrics

Degree of IE autonomy

Page 13: Intelligent Environments1 Conclusions and Future Directions

Intelligent Environments 13

Special Topics Intelligent robotic sensor agents

for environment monitoring Intelligent vehicles Personalization (e.g., television

guides) Context-aware applications Intelligent agent infrastructures

Page 14: Intelligent Environments1 Conclusions and Future Directions

Intelligent Environments 14

Future Directions Smart appliances Plug-n-play everything (devices

and software) Ubiquitous/pervasive computing

Low-power, wireless, smart sensors Low-power, wireless networks Distributed, active databases

Page 15: Intelligent Environments1 Conclusions and Future Directions

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Future Directions Prediction and decision-making in

uncertain, data-rich environments Distributed, hierarchical, self-

organizing, agent-based architectures

Versatile robotics Adaptive security and biometrics Virtual reality

Page 16: Intelligent Environments1 Conclusions and Future Directions

Intelligent Environments 16

Future Directions “Killer App”

Support for the handicapped and elderly Generalization to larger environments

Communities Office buildings Shopping centers Cities Streets and highways

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Intelligent Environments 17

Intelligent Environments

Thank you!