A Portable Object Detection System for Visually Impaired Individuals in Outdoor Environments

In recent years, progress in machine learning methods has greatly influenced the creation of assistive technologies designed to enhance the quality of life for individuals with visual impairments. This paper introduces a unique real-time image analysis method specifically developed for the visually impaired community. Leveraging the You Only Look Once (YOLO) dataset and machine learning algorithms implemented in Python, our The suggested system provides a seamless and efficient solution for identifying objects in the circumventing environment in genuine-time. In this study, we performed comprehensive experiments to assess the effectiveness of our system, taking into account aspects like detection accuracy, processing speed, and usability for users with visual impairments. The results demonstrate the efficacy and reliability of our approach in genuine-world scenarios, showcasing its potential to be accommodated as a valuable and implement for improving autonomy and mobility of visually impaired individuals.