Intelligent Environments1 Conclusions and Future Directions.

Slides:



Advertisements
Similar presentations
OneM2M Technical Requirements - Driven by EU BUTLER and IEEE PAC - Group Name: WG1 (REQ) Source: Friedbert Berens, FBConsulting Sarl,
Advertisements

Intelligent Environments1 Computer Science and Engineering University of Texas at Arlington.
Vikramaditya Jakkula Washington State University First International Workshop on Smart Homes for Tele-Health.
. Smart Cities and the Ageing Population Sustainable smart cities: from vision to reality 13 October ITU, Geneva Knud Erik Skouby, CMI/ Aalborg University-Cph.
Intelligent Environments1 Computer Science and Engineering University of Texas at Arlington.
Introduction to HCC and HCM. Human Centered Computing Philosophical-humanistic position regarding the ethics and aesthetics of a workplace Any system.
PhD course - Milan, March /06/ Some additional words about pervasive/ubiquitous computing Lionel Brunie National Institute of Applied Science.
Kjeld Svidt, Aalborg University Intelligent Buildings - a short overview Kjeld Svidt December 2003.
Real-Time Systems and the Aware Home Anind K. Dey Ubiquitous Computing Future Computing Environments.
Master Course /06/ Some additional words about pervasive/ubiquitous computing Lionel Brunie National Institute of Applied Science (INSA)
Robotics for Intelligent Environments
SensIT PI Meeting, April 17-20, Distributed Services for Self-Organizing Sensor Networks Alvin S. Lim Computer Science and Software Engineering.
Research Directions for the Internet of Things Supervised by: Dr. Nouh Sabry Presented by: Ahmed Mohamed Sayed.
EHealth Challenges and Opportunities E-health: Multi-disciplinary of E (ICT) and Healthcare, or applied ICT in healthcare (Design oriented), or healthcare.
Wireless Sensor Networks Smart Environments: Technologies, Protocols, and Applications ed. D.J. Cook and S.K. Das, John Wiley, New York, B.Devi
Computer Science and Engineering Department The University of Texas at Arlington MavHome: An Intelligent Home Environment.
Intelligent Agents: an Overview. 2 Definitions Rational behavior: to achieve a goal minimizing the cost and maximizing the satisfaction. Rational agent:
Smart Home Technologies CSE 4392 / CSE 5392 Spring 2006 Manfred Huber
Sharena Paripatyadar.  What are the differences?
Help or Hal? Smart Homes & Elderly Care. Smart Homes A smart home (sometimes referred to as a smart house or eHome) is one that has highly advanced automatic.
AMBIENT INTELLIGENCE Presented by GOKUL SURESH. INTRODUCTION  Evolution of Ambient Intelligence.  Science with a fictional view.  Enriching environment.
Agent-based E-travel Agency Agent Systems Laboratory Oklahoma State University
Self-Organizing Adaptive Networks Hari Balakrishnan MIT Laboratory for Computer Science
An Intelligent Broker Architecture for Context-Aware Systems A PhD. Dissertation Proposal in Computer Science at the University of Maryland Baltimore County.
A Survey on Context-Aware Computing Center for E-Business Technology Seoul National University Seoul, Korea 이상근, 이동주, 강승석, Babar Tareen Intelligent Database.
Component 4: Introduction to Information and Computer Science Unit 10: Future of Computing Lecture 2 This material was developed by Oregon Health & Science.
Chapter 8 Prediction Algorithms for Smart Environments
Computational & Information Science Division Tuesday, May 17, 2005 Randy Zachery, ARO.
IT 351 Mobile &Wireless Computing Semester 2, Dr. Hala Mokhtar Room 79- 2nd floor.
Component 4: Introduction to Information and Computer Science Unit 10b: Future of Computing.
Vikramaditya Jakkula Washington State University IEEE Workshop of Data Mining in Medicine 2007 (DMMed '07) In conjunction with IEEE.
CPET 565 Mobile Computing Systems Context-Aware Computing (2) Lecture 11 Hongli Luo Indiana University-Purdue University Fort Wayne.
Weems CSE  CompE Transition 2007 BSCSE PRE-PROFESSIONAL (54 hours) GENERAL EDUCATION (24 hours) PROFESSIONAL (49 hours) 3302 Programming Languages 3310.
Usability in Pervasive Computing Environment Advance Usability October 18, 2004 Anuj A. Nanavati.
Chapter 17 Challenges & The Future The Future Technologies - what we can do Desires - what we want Emerging Technologies - what we think we can.
Middleware for Grid Computing and the relationship to Middleware at large ECE 1770 : Middleware Systems By: Sepehr (Sep) Seyedi Date: Thurs. January 23,
Cerberus: A Context-Aware Security Scheme for Smart Spaces presented by L.X.Hung u-Security Research Group The First IEEE International Conference.
Context Aware Toolkit 1 ©Jason Prideaux What is Context-Aware Computing?  Some definitions: Context: The physical and social situation in which the person/
Introduction to Networked Robotics CS 643 Seminar on Advanced Robotics Wenzhe Li, Graduate Student Texas A&M University.
Computing Ontology Part II. So far, We have seen the history of the ACM computing classification system – What have you observed? – What topics from CS2013.
Master Course /11/ Some additional words about pervasive/ubiquitous computing Lionel Brunie National Institute of Applied Science (INSA)
1 Ubiquitous Computing Nov. 15, 2006 Ki-Joune Li.
Application of Operating System Concepts to Coordination in Pervasive Sensing and Computing Systems Benjamin J. Ewy, Larry M. Sanders Ambient Computing,
Semantic Gadgets Pervasive Computing Meets the Semantic Web Reza Zakeri Sharif University of Technology.
REU 2004 Computer Science and Engineering Department The University of Texas at Arlington Research Experiences for Undergraduates in Distributed Rational.
 Problem Definition  Presented by Sushant and Alex Overview of the problem space Scenario Issues Example (plant care example) Discussion conclusion open.
Presented by Darshan Balakrishna Shetty. Contents Internet of Things? Sample IoT devices What's Smart? Why Now? IoT in Power Grids and Homes Smart Grid.
Mobile Computing and Wireless Communication Pisa 26 November 2002 Roberto Baldoni University of Roma “La Sapienza”
Realization of Home Appliances Control System based on Power Line Communication Technology.
REU 2007 Computer Science and Engineering Department The University of Texas at Arlington Research Experiences for Undergraduates in Information Processing.
Feb 12, ECET 581/CPET/ECET 499 Mobile Computing Technologies & Apps Context Aware Computing 3 of 3 Lecture 12 Paul I-Hai Lin, Professor Electrical.
Semantic Web in Context Broker Architecture Presented by Harry Chen, Tim Finin, Anupan Joshi At PerCom ‘04 Summarized by Sungchan Park
Ambient Intelligence: Everyday Living Aid System for Elders
Computer Science and Engineering Department The University of Texas at Arlington MavHome: An Intelligent Home Environment.
Control-Theoretic Approaches for Dynamic Information Assurance George Vachtsevanos Georgia Tech Working Meeting U. C. Berkeley February 5, 2003.
REU 2009 Computer Science and Engineering Department The University of Texas at Arlington Research Experiences for Undergraduates in Information Processing.
Cyberinfrastructure Overview of Demos Townsville, AU 28 – 31 March 2006 CREON/GLEON.
Data Mining for Hierarchical Model Creation G. Michael Youngblood and Diane J. Cook IEEE Transactions on Systems, Man, and Cybernetics, Part C, 37(4): ,
Computer Science and Engineering Department The University of Texas at Arlington MavHome: An Intelligent Home Environment.
Internet of Things – Getting Started
CASAS Smart Home Project Center for Advanced Studies in Adaptive Systems Washington State University.
AUTONOMIC COMPUTING B.Akhila Priya 06211A0504. Present-day IT environments are complex, heterogeneous in terms of software and hardware from multiple.
MetaOS Concept MetaOS developed by Ambient Computing to coordinate the function of smart, networked devices Smart networked devices include processing.
1st Draft for Defining IoT (1)
Chapter 1 -- Overview Technologies Standards Algorithms Protocols
Ambient Intelligence -by Internal Guide: M.Preethi(10C91A0563)
Ambient Intelligence.
Mobile Computing.
Abhishek Bhola Bharati Vidyapeeth University, College of Engineering
Copyright 2005 Prentice- Hall, Inc.
Presentation transcript:

Intelligent Environments1 Conclusions and Future Directions

Intelligent Environments2 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 Environments3 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

Intelligent Environments4 Major Topics Sensors Networking Database Prediction Decision Making Robotics Privacy and Security

Intelligent Environments5 Sensors Issues Placement Power Interfacing Control Smart sensors Local memory Local processing Communication

Intelligent Environments6 Networking Wired Phone line Power line New wire Wireless IEEE Bluetooth

Intelligent Environments7 Networking (cont.) Service Discovery Jini UPnP Communication CORBA Java-RMI DCOM

Intelligent Environments8 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

Intelligent Environments9 Prediction Predicting inhabitant and environment behavior Sensor fusion and data relevance Concept drift IE-specific prediction Sequence matching Hidden Markov models Episode discovery

Intelligent Environments10 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

Intelligent Environments11 Robotics Robotics for IE Autonomy Adaptability Human-machine interfacing

Intelligent Environments12 Privacy and Security Physical and data security Encryption Firewalling Biometrics Degree of IE autonomy

Intelligent Environments13 Special Topics Intelligent robotic sensor agents for environment monitoring Intelligent vehicles Personalization (e.g., television guides) Context-aware applications Intelligent agent infrastructures

Intelligent Environments14 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

Intelligent Environments15 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

Intelligent Environments16 Future Directions “Killer App” Support for the handicapped and elderly Generalization to larger environments Communities Office buildings Shopping centers Cities Streets and highways

Intelligent Environments17 Intelligent Environments Thank you!