Implementation of Smart Glasses for Blind Persons Using Raspberry Pi

This project aims to develop an assistive system for visually impaired individuals using a Raspberry Pi, OpenCV, and TensorFlow. The system integrates facial recognition, object detection, and obstacle sensing to enhance navigation and interaction with the environment. Facial recognition identifies familiar individuals, providing social interaction assistance, while object detection identifies common objects in real-time to improve spatial awareness. An ultrasonic sensor detects nearby obstacles and alerts the user through audio or vibration feedback, ensuring safer navigation. The system employs Convolutional Neural Networks (CNNs), a deep learning model optimized for image processing, to handle tasks such as object detection and text-to-speech conversion. Additionally, the system includes a wearable smart glasses prototype that scans text images and converts them into audio, delivered through connected headphones, addressing educational barriers. This invention seeks to motivate blind students to complete their education by overcoming navigational and informational challenges, with potential applications in daily life and educational settings.

Assistive technology, visually impaired, Raspberry Pi

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