Integrated Face Counting and Quick Response (QR) Object Detection with Voice-Based Alerts: A Smart Vision System

Visually impaired persons (VIPs) face significant navigation challenges both indoors and outdoors, including difficulty detecting obstacles, locating essential amenities, and orienting themselves in unfamiliar environments. By addressing these challenges comprehensively and inclusively, the lives of visually impaired individuals can be enhanced significantly, fostering their independence, safety, and social inclusion. This paper presents an innovative application designed to assist visually impaired individuals in navigating their surroundings through advanced object and person recognition technologies. Utilizing a combination of machine learning algorithms and QR code scanning, the application enables users to identify the number of people standing in front of them and recognize objects by reading their corresponding QR codes. By converting visual information into audible cues, the application fosters independence and enhances the overall mobility of blind users in various environments. The integration of real-time processing and user-friendly interfaces demonstrates the potential for technology to significantly improve the quality of life for visually impaired individuals.