ARCHIVES
Design and Implementation of an AI-Based Assistive Smart Glass System for Visually Impaired with Real-Time Object Detection and Emergency Alert
1 2 3 4 5 Department of Electronics Engineering, Dr. Panjabrao Deshmukh Polytechnic, Amravati, Maharashtra, India. 6 HOD of Electronics Engineering, Dr. Panjabrao Deshmukh Polytechnic, Amravati, Maharashtra, India.
Published Online: January-April 2026
Pages: 42-48
Visual impairment is a major global challenge that restricts independent mobility, environmental awareness, and personal safety. Traditional assistive devices provide limited support and lack intelligent perception and emergency handling capabilities. This work presents a vision-based assistive safety system developed using Raspberry Pi to enhance independence and safety for visually impaired individuals. This work proposes a vision-driven assistive system designed to improve mobility and safety for visually impaired individuals. The system combines real-time face recognition using the LBPH algorithm with object detection based on the YOLOv3-Tiny deep learning model to identify people and surrounding objects. Audio feedback is provided through a text-to-speech engine for user guidance. A GPS module continuously tracks live location, which is displayed through a web interface, while a touch-based emergency mechanism sends alert emails with a Google Maps location link to a caretaker. The system operates in real time using multithreading and demonstrates reliable performance in assistive and emergency scenarios, making it suitable for real-world applications.
