Human Identification and Obstacle Detection System for Blind
Bhuvanesh, Sreerambabu, Nimmy Pailochan, Kalidasan · International Journal for Research in Applied Science and Engineering Technology · 2023
Abstract: According to the World Health Organization (WHO), there are millions of visually impaired individuals worldwide in detecting obstacles and identifying people. It emphasizes the advancements in information technology and spatial cognition theory for visually impaired individuals as a new opportunity. The prototype proposes a simple and cost-effective solution using artificial vision through an AI-based intelligent system. The system utilizes the Faster Region Convolutional Neural Network (FRCNN) architecture to recognize human and scene objects or obstacles in real-time, even in complex environments. It provides users with comprehensive information about the presence, position, and nature of targets, and uses voice messages to alert blind individuals about obstacles or people nearby. The goal is to create a user-friendly technology that facilitates communication and independence for visually impaired individuals, enabling them to navigate both indoor and outdoor locations effectively.