ANVAYA: AI-powered Navigation & Vision-based Assistive System for the Visually Impaired

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@article{1718861,
      author = {Maddala Tabitha Angel, Grishma Harisha, Sinchana K S, Vardhini M, Dr. Kavitha Devi C S},
      title = {ANVAYA: AI-powered Navigation & Vision-based Assistive System for the Visually Impaired},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {12},
      pages = {1454-1461},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1718861.pdf},
      abstract = {Visual impairment significantly affects an individual’s ability to navigate safely due to limited perception of surrounding obstacles and environmental conditions. Traditional mobility aids such as white canes provide reliable ground-level obstacle detection but lack forward-looking spatial awareness, while many existing assistive systems focus primarily on object detection without delivering effective navigation guidance. This paper presents ANVAYA, a real-time assistive navigation system that integrates computer vision and ultrasonic sensing through sensor fusion to enhance environmental perception. A lightweight deep learning model is employed for object detection, while ultrasonic sensors provide accurate distance estimation for nearby obstacles. The proposed system introduces a zone-based spatial risk assessment model combined with a priority-driven decision framework to generate real-time directional guidance. Based on the assessed risk level, an adaptive multimodal feedback mechanism delivers context-aware audio and haptic alerts, enabling users to respond effectively while reducing cognitive load. The system is implemented on an embedded platform to ensure portability, low-latency operation, and practical usability in real-world environments. Experimental evaluation demonstrates improvements in obstacle detection accuracy, navigational responsiveness, and user safety, highlighting the potential of ANVAYA as an effective assistive solution for individuals with visual impairments.},
      keywords = {Accessibility, Assistive Navigation, Computer Vision, Embedded Systems, Multimodal Feedback, Object Detection, Real-Time Systems, Sensor Fusion, Visually Impaired.},
      month = {June},
      doi = {https://doi.org/10.64388/IREV9I12-1718861}
  }