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Blind Guide (BG) 👁️

Blind Guide (BG): AI-Powered Assistive Mobile Application is an application created to help the blind and visually impaired facilitate their lives and deal with the surrounding environment. The primary goal of this application is to make blind people fit more properly in the society.

Technical Highlights

  • Advanced AI Vision: Developed a cross-platform app using Flutter and TensorFlow Lite, implementing a Faster R-CNN model for real-time object and facial recognition.
  • Hybrid Navigation System: Engineered a hybrid navigation system combining smartphone cameras with Ultrasonic sensors and a gesture-based UI to ensure safe, menu-free obstacle avoidance.
  • Field Testing: Validated system performance and user accessibility at King Fahad Eye Specialist Hospital in Jeddah to align technical outputs with clinical patient needs.

Problem Statement

Many blind people cannot practice their lives normally because of their visual impairment. They frequently face the following daily challenges:

  • It is difficult for them to move in the presence of obstacles.
  • They face difficulties to read texts.
  • They struggle with determining the color of clothes and others.

Features

This application provides several key features to assist users:

  • Object Detection: Identifies surrounding objects to help users navigate safely.
  • Color Detection: Helps users determine the colors of everyday items.
  • Text Recognition: Scans and reads texts aloud for the user.
  • Emergency Call: Provides quick access to emergency contacts.
  • Motion Sensor: Utilizes sensors to detect motion and obstacles.
  • Audio Onboarding: Helps to explain the application features with sound in Arabic.

Technologies Used

This application uses the following technologies:

  • Framework: Flutter Framework
  • Programming Language: Dart Language
  • AI & Machine Learning: TensorFlow Lite, Faster R-CNN
  • Hardware Integration: Ultrasonic Sensors
  • Additional Integrations: Web Development

Team & Supervision

This project was developed under the supervision of Dr. Mohammed Al-Hamed.

Prepared by:

  • Mohammed Alnami
  • Turki Abbas
  • Abdullah Alshere

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Innovative Navigation Assistance for the Visually Impaired

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