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Visually impaired people and blind people are the people who need the benefits of assistive technologies to a great extent. They always rely on another person’s help. But by using assistive technologies, people can minimize their dependencies to a greater extent. Most of the research that is going on in this domain is highly dependent on hardware design, which is a drawback in the long run. In this paper, a system is proposed that relies predominantly on software, minimizing hardware dependencies and thereby facilitating easier updates. In the proposed system, a cloud-based app that can be easily downloaded onto the respective mobile devices or can be used in web mode. To use the app in its peak productivity, users may pair hardware devices through Bluetooth. Without pairing hardware devices, it can work in a minimal mode by incorporating the mobile camera. The additional hardware devices may include Bluetooth cameras and sensors to determine the distance. The user can select which hardware should be used. The system under consideration employs cutting-edge technologies like YOLO, OpenCV, and Large Language model (LLM) for giving a better experience for the user.

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Minimizing Hardware Dependency and Enhancing Independence for the Visually Impaired and Blind People Using LLM and Computer Vision

  • 会议论文

  • 发表日期：

    2026年

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  • Poli Lokeshwara Reddy,
  • A. Sujith Kumar,
  • Chanda Shreyas,
  • Vemula Gurumurthy

摘要

Visually impaired people and blind people are the people who need the benefits of assistive technologies to a great extent. They always rely on another person’s help. But by using assistive technologies, people can minimize their dependencies to a greater extent. Most of the research that is going on in this domain is highly dependent on hardware design, which is a drawback in the long run. In this paper, a system is proposed that relies predominantly on software, minimizing hardware dependencies and thereby facilitating easier updates. In the proposed system, a cloud-based app that can be easily downloaded onto the respective mobile devices or can be used in web mode. To use the app in its peak productivity, users may pair hardware devices through Bluetooth. Without pairing hardware devices, it can work in a minimal mode by incorporating the mobile camera. The additional hardware devices may include Bluetooth cameras and sensors to determine the distance. The user can select which hardware should be used. The system under consideration employs cutting-edge technologies like YOLO, OpenCV, and Large Language model (LLM) for giving a better experience for the user.