Build an E-Glass for the Blinds

Slides:



Advertisements
Similar presentations
Pseudo-Relevance Feedback For Multimedia Retrieval By Rong Yan, Alexander G. and Rong Jin Mwangi S. Kariuki
Advertisements

Advanced Speech Enhancement in Noisy Environments
Types of Computers & Computer Hardware
Types of Computers & Computer Hardware Computer Technology.
Distance Education Podcasting with Special Education Students Spring 2009 Matt Dockery.
Implementing 3D Digital Sound In “Virtual Table Tennis” By Alexander Stevenson.
EE491D Special Topics in Communications Adaptive Signal Processing Spring 2005 Prof. Anthony Kuh POST 205E Dept. of Elec. Eng. University of Hawaii Phone:
1 Department of Electrical and Computer Engineering Advisor: Professor Zink Team Acoustic Beamformer Preliminary Design Review 10/18/2013.
Applications of Signals and Systems Fall 2002 Application Areas Control Communications Signal Processing.
(Need, scope & Applications) Gurpreet Kaur, Assistant Professor, ECE Department, CTIEMT.
M. Guymon Pleasant Grove High Spring 2003 Types of Computers & Computer Hardware Computer Technology Day 1.
Assistive Technology Ability to be free. Quick Facts  Assistive technology is technology used by individuals with disabilities in order to perform functions.
Performed by : Matan Cohen & Sefi Cohen Instructor: Mony Orbach המעבדה למערכות ספרתיות מהירות High speed digital systems laboratory הטכניון - מכון טכנולוגי.
Applications of Signals and Systems Application Areas Control Communications Signal Processing (our concern)
Vehicle License Plate Detection Algorithm Based on Statistical Characteristics in HSI Color Model Instructor : Dr. K. R. Rao Presented by: Prasanna Venkatesh.
2010/12/11 Frequency Domain Blind Source Separation Based Noise Suppression to Hearing Aids (Part 1) Presenter: Cian-Bei Hong Advisor: Dr. Yeou-Jiunn Chen.
Group Members: Sam Marlin, Jonathan Brown Faculty Adviser: Tom Miller.
Advanced Topics in Speech Processing (IT60116) K Sreenivasa Rao School of Information Technology IIT Kharagpur.
MULTIMEDIA INPUT / OUTPUT TECHNOLOGIES INTRODUCTION 6/1/ A.Aruna, Assistant Professor, Faculty of Information Technology.
Artificial Intelligence 2004 Speech & Natural Language Processing Speech Recognition acoustic signal as input conversion into written words Natural.
AN INTELLIGENT ASSISTANT FOR NAVIGATION OF VISUALLY IMPAIRED PEOPLE N.G. Bourbakis*# and D. Kavraki # #AIIS Inc., Vestal, NY, *WSU,
Types of Computers & Computer Hardware Computer Technology Day 1.
ARTIFICIAL INTELLIGENCE FOR SPEECH RECOGNITION. Introduction What is Speech Recognition?  also known as automatic speech recognition or computer speech.
R. Stewart Fayetteville High School Types of Computers & Computer Hardware Computer Technology.
Visual Information Processing. Human Perception V.S. Machine Perception  Human perception: pictorial information improvement for human interpretation.
How can speech technology be used to help people with disabilities?
Intelligent Transportation System
Face Detection and Notification System Conclusion and Reference
Electrical Engineering
Information Computer Technology
Information Computer Technology
Introduction to Pattern Recognition
Chapter 17: Measure Up! How to Measure Your Results
Fundamentals of Information Systems
Types of Computers & Computer Hardware
Alaa Omar Rana Diab Supervised by Dr.Raed Jaber
Types of Computers & Computer Hardware
DBS INSTITUTE OF TECHNOLOGY
A Support Vector Machine Approach to Sonar Classification
Course Projects Speech Recognition Spring 1386
ABSTRACT FACE RECOGNITION RESULTS
Abstract (may be neglected) Results and Discussions
Chapter 2: Input and output devices
                      Digital Audio 1.
ARTIFICIAL INTELLIGENCE.
Introduction to Deep Learning for neuronal data analyses
Kocaeli University Introduction to Engineering Applications
ECE Computer Engineering Design Project
Home Automation Enhancement with EEG Based Headset (Orpheus)
Introduction to IT and Types of Computers
Introduction Brain driven car which would be of great help to the physically disabled people. These cars will rely only on what the individual is thinking.
Lecture 16 Figures from Gonzalez and Woods, Digital Image Processing, Second Edition, 2002.
The Beauty of Mathematics in
Engineering Tools for Electrical and Computer Engineers
ISCA Distinguished Lecture
Project Schematics Circuit Working Principle and Equations
Project Schematics Circuit Working Principle and Equations
3.1.1 Introduction to Machine Learning
TECHNOLOGICAL PROGRESS
Zip Codes and Neural Networks: Machine Learning for
Self Driving Car Market Self Driving Car Market.
Self Driving Car Market Self Driving Car Market.
Digital Systems: Hardware Organization and Design
John H.L. Hansen & Taufiq Al Babba Hasan
Machine Vision By: Reza Ebrahimpour 2009
MBA 231 RESEARCH METHODOLOGY Course Introduction Dr. Mohammed Al-Abed.
Artificial Intelligence
Wadner Joseph • James Haralambides, PhD Abstract
Chapter 0 Introduction Introduction Chapter 0.
Presentation transcript:

Build an E-Glass for the Blinds Using Information Technology and Artificial Intelligence to Build an E-Glass for the Blinds KHALED AL-SARAYREH, RAFA E. AL-QUTAISH The Higher Council for Affairs of Persons with Disabilities JORDAN rafa@ieee.org, khalid_sar@asu.edu.jo

Abstract IT and communication systems are used in a wide range of our lives. Therefore, we can not imagine our lives without IT and communication systems. From this point we got an idea to build an e-glass which utilizes of an embedded system and neural networks, however, this e-glass could be used by the blinds to assist them in their ways without any assistants from other persons. thus improving their mobility and independent living

Abstract It is important to note that the hardware and software components of the e-glass are not expensive. When this glass is used by the blinds it will make them self confidence, let them walk independently and increase their morale.

Introduction The idea of building an e-glass it will be treated as a first step in using the technology as an integrated or replaceable part of the damaged human neural system; this will help to make the life easier for the blinds.

Introduction The proposed e-glass works through an electronic circuit to scan and collect information about the entire object which could be found in front of the blind, then it will analyse these objects to give a voice command to the blind to keep away from these obstacles (objects).

General View of the E-Glass This e-glass works through the ultra sonic waves by sending radar signals for distance from 2 meter to 50 meters and 120 degrees as a vertical and horizontal cover angle along with 60 degrees to cover the right and left, as a result, in total the cover angle will be 270 degrees. Therefore, after receiving the information from the radar system, they will be analyzed in the artificial intelligence software and produce a warning about any obstacle objects through a headphone.

General View of the E-Glass The characteristics of this e-glass is that it can identify any small object with a 2 cm2 area or more from 2 meters distance. As a future work, this e-glass could be embedded to the electronic devices within the cars. In addition, we can develop the embedded electronic circuit programs to receive the neural flows from the human brain and use the pattern recognition to analyse the objects as images.

How the E-Glass Works? First phase: putting the receiver (radar) on the glass and analysing all the data which are collected from the radar, this analysis could be done through the first electronic circuit programs, then an electronic signal will be sent to the electronic warning and alarming device (the headphone).

How the E-Glass Works? Second phase: the electronic signal will be sent from the first electronic circuit to the second electronic circuit which has the artificial intelligence system to give a scaled warning based on the dangerous degree.

E-Glass Electronic Circuit Figure 1: The E-Glass Embedded System.

E-Glass Electronic Circuit Figure 2: The Electronic Scanning System to Tackle the Objects.

E-Glass Electronic Circuit Figure 3: Sending and Receiving Signals Timing System.

E-Glass Electronic Circuit Figure 4: The Completed E-Glass Electronic Circuit.

Conclusion The research in the filed of using IT to assist the special needs person is little which make it distinctive work from the social view. Therefore, within research we just started a huge work to make the life of the special needs person easier.

References 1. B. Gold and N. Morgan, Speech and Audio Signal Processing: Processing And Perception of Speech and Music, John Wiley & Sons, Inc., New York, 2000 2. Do Minh N., "An Automatic Speaker Recognition System," Audio Visual Communications Laboratory Swiss Federal Institute of Technology, Lausanne, Switzerland, 3. EE 578 Digital Speech Processing, Levant Arslan’s lecture notes, Spring 2001, Boðaziçi University, Turkey 4. G. Fant, Acoustic Theory of Speech Production, Mouton & Co., The Hague, 1970 And Some of its Implications”, Journal of Speech and Hearing Research, 4:303-320, 1961 5. (Gonzalez, 2002) Gonzales, Rafael. and Woods, Richard. 2002. Digital image processing, second edition, Prentice-hall. 6. (Guo and Liddell, 2002) Guo, S. and Liddell, H. 2000. Support Vector Regression and Classification Based Multi-view Detection and Recognition IEEE International Conference on Automatic Face& Gesture Recognition, pp.300-305.

References 7. J.H.L. Hansen, Slides for ECEN-5022 Speech Processing & Recognition, University of Colorado Boulder, 2000, 8. J.R.Deller, J.G Proakis.J.H.Hansen.Discrete-Time Processing of Speech Signals, Macmillan, New York 1993. 9. K.N. Stevens and A.S. House, “An Acoustic Theory of Vowel Production 10. “Matlab VOICEBOX” http://www.ee.ic.ac.uk/hp/staff/dmb/voicebox/voicebox.html 11. Mihn Doh, “An Automatic Speaker Recognition System” http://lcavwww.epfl.ch/~minhdo/asr_project/asr_project.html 12. Mohamed Gasem, “Vector Quantization” http://www.geocities.com/mohamedqasem/vectorquantization/vq.html 13. S.B. Davis and P. Mermelstein, "Comparison of parametric representations for Monosyllabic word recognition in continuously spoken sentences", IEEE