EYERIS_ A Virtual Eye to Aid the Visually Impaired

EYERIS_ A Virtual Eye to Aid the Visually Impaired

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Product Description

Aim:

Aim of this project is to develop a personal assistant system for deaf-blind people to help identify faces of people and objects in terms of Morse code.

Synopsis:

          In the era of artificial intelligence lot of object and face detection devices are available for visually impaired people. When it comes to subject of deaf-blind people there is none of devices available in market. For them, only communication devices like MyVox, Sparsha are available rather than personal assistive devices. In this project we are going to propose a personal assistive device to help deaf-blind people using Machine learning and Morse code.

            It consists of multiple in-built options like object detection, facial recognition and communication module. For object detection, we are using Machine learning objection detection model which is trained by CNN algorithm. It can detect multiple objects at same time and detected objects name is intimated to user by tactile vibrations. For face detection, first we are collecting dataset and trained them into CNN model. Using this model we can recognize trained faces and can intimated user when only device in face identification mode. To make communication between users with other people we are using Google speech recognition and text to speech conversion. Every text appeared in the module is converted into Morse code to make corresponding tactile vibrations.

Proposed System:

          Proposed system utilizes the Morse code to convert every text into vibrations using micro vibrators. Buttons are used to generate Morse code by user and converted into audio. For object detection, tflite model is used instead of conventional machine learning models. tflite model helps to increase the frame rate while using ARM based microprocessors.

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Package Includes

Software Projects Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. UML Diagrams
  6. SRS
  7. Source Code
  8. Screen Shots
  9. Software Links
  10. Reference Papers
  11. Full Project Documentation
  12. Online support


The Delivery time for software projects is 2 -3 working days. Some of the software projects will require Hardware interface. Please go through the hardware Requirements in the abstract carefully. The Hardware will take 7-8 Working Days

 

Hardware Projects Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. Datasheets
  6. Circuit Diagrams
  7. Source Code
  8. Screen Shots & Photos
  9. Software Links
  10. Reference Papers
  11. Lit survey
  12. Full Project Documentation
  13. Online support


The Delivery time for Hardware projects is 7-8 working days.

   

Mini Projects: Software Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. UML Diagrams
  6. SRS
  7. Source Code
  8. Screen Shots
  9. Software Links
  10. Reference Papers
  11. Full Project Documentation
  12. Online support

 

The Delivery time for software Miniprojects is 2 -3 working days.

 

Mini Projects - Hardware includes

  1. Demo  Video
  2. Abstract
  3. PPT
  4. Datasheets
  5. Circuit Diagrams
  6. Source Code
  7. Screen Shots & Photos
  8. Software Links
  9. Reference Papers
  10. Full Project Documentation
  11. Online support

The Delivery time for Hardware Mini projects is 7-8 working days.