Assisting blind people with AI and audio using smart glasses: system design with YOLOv8 variants comparisons

This paper introduces a novel system design leveraging Vuzix Blade 2 smart glasses to enhance the mobility and independence of visually impaired individuals. The study critically examines existing assistive navigation and object detection technologies, identifying their limitations and gaps. The designed system integrates real-time object detection, distance estimation, and OCR functionalities, providing auditory feedback through a robust and efficient pipeline. The designed application enhances the independence and safety of visually impaired individuals, particularly in navigating university campuses. A dataset comprising 15,951 annotated images from the university campus was used for training and evaluation. A comparative analysis of three YOLOv8 models (YOLOv8-N, YOLOv8-S, and YOLOv8-M) was conducted, balancing accuracy and computational efficiency to optimise system performance. The pipeline also offers a comprehensive framework for developers and researchers to build inclusive systems combining AR, computer vision, and AI. Results show high object detection accuracy (precision: 0.90, recall: 0.83) and reliable distance estimation with a minor error of 0.33 m. Results demonstrate the system’s capability to detect obstacles within one meter, provide precise distance estimation, and convert textual information into speech, validating its potential for real-world applications. This study emphasises the significant role of AI-driven solutions in advancing assistive technologies, paving the way for more accessible and inclusive navigation systems. Compared with recent assistive systems such as Smart Cane (He in CCF Trans. Pervasive Comput. Interact. 5:382–395, 2023), OrCam MyEye (Amore in J. Med. Syst. 47:11, 2023), and IrisVision (Gopalakrishnan in Comparison of visual function analysis of people with low vision using three different models of augmented reality devices, 2024), the proposed system demonstrates superior integration of detection, text recognition, and real-time feedback within a lightweight wearable device.