Visioneer: AI Guided Navigation for the Visually Impaired

Abstract

Navigating independently in an unfamiliar environment poses significant challenges for individuals with visual impairments. Traditional aids like canes and guide dogs, while helpful, offer limited contextual awareness and situational understanding. This project, titled \"Visioneer: AI-Guided Navigation for Visually Impaired,\" aims to bridge this gap through an intelligent, real-time assistive system that leverages advancements in Artificial Intelligence, Computer Vision, and Wearable Technology. The proposed solution is a pair of AI-enabled smart glasses integrated with a camera and a speaker, capable of detecting obstacles, identifying key landmarks, and delivering navigational cues via audio prompts. The system transforms visual data into meaningful auditory instructions, enabling users to move confidently and safely in dynamic environments. At the core of the system lies the YOLO (You Only Look Once) object detection algorithm, which enables rapid and accurate identification of objects in the user\'s path. OpenCV is utilized for real-time image processing, enhancing the system\'s ability to interpret the environment efficiently. To provide seamless audio feedback, the pyttsx3 text-to-speech library is integrated, converting recognized objects and spatial cues into speech output. This combination of technologies ensures that the system remains both fast and functional, operating smoothly on portable hardware. By enhancing situational awareness and reducing dependency on others, the AI-Guided Navigation system empowers visually impaired individuals with a greater sense of autonomy, offering a practical, scalable solution for inclusive navigation.

Introduction

Visual impairment significantly limits an individual's ability to navigate and interact with their environment, making everyday tasks challenging. Traditional aids like white canes and guide dogs offer limited assistance, primarily due to their dependence on physical proximity and inability to provide real-time, contextual information.

The “Visioneer: AI-Guided Navigation for Visually Impaired” project addresses these challenges by developing a wearable, AI-powered navigation system embedded in glasses. It uses a front-facing camera combined with the YOLO object detection algorithm, OpenCV for image processing, and the pyttsx3 text-to-speech engine to detect obstacles and key objects, and communicate this information through audio cues in real-time. This system aims to improve independence, safety, and confidence for visually impaired users.

The project is motivated by the limitations of existing mobility aids and seeks to leverage advances in AI, computer vision, and embedded systems to provide a low-cost, portable, and offline-capable assistive device. The system focuses on real-time object detection with minimal latency on embedded hardware to enhance navigation in various environments.

The broader significance of Visioneer lies in its potential to promote inclusivity, accessibility, and independence for visually impaired individuals globally. It aligns with sustainable development goals by reducing inequalities and offering an affordable, user-friendly solution compared to expensive or internet-dependent alternatives.

The literature review highlights existing navigation aids and AI-based systems, noting their limitations such as reliance on sensors, RFID infrastructure, high computational demands, internet dependency, and privacy concerns, which Visioneer seeks to overcome.

Finally, the Software Requirements Specification outlines the system’s functional components—including real-time object detection, image processing, text-to-speech conversion—and hardware/software interfaces, emphasizing the importance of real-time performance, reliability, ease of use, and offline operation.

Conclusion

The ability to perceive and interact with the surrounding environment through vision is something most people take for granted. For individuals with visual impairments, however, the absence or limitation of sight brings about significant challenges in performing even the most routine daily tasks—particularly those involving navigation and spatial awareness. Walking in public spaces, identifying obstacles, locating landmarks, and reacting to dynamic situations are all activities that become considerably more complex without visual input. Traditional mobility aids such as white canes and guide dogs offer a level of assistance, but their capabilities are inherently limited. These aids rely heavily on physical proximity and cannot provide comprehensive, real-time information about the surroundings, which is critical for safe and confident navigation.

References

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Copyright

Copyright © 2025 Mohamed Areeb, Siddharth Kumar, Bhagyashree Patil. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.