Ai Powered Wearable Assistant For Visually Impaired People

• Author(s):

  Abina M S | Dharshini R | Janani B | Bhavadharani S

• Keywords:

  Artificial Intelligence, Wearable Technology, Computer Vision, CNN, OCR, Assistive Technology, Visually Impaired

• Abstract:

  Blind And Visually Impaired Individuals Face Continuous Challenges In Their Everyday Lives, Especially When Identifying People, Detecting Obstacles, And Recognizing Currency, Which Significantly Affects Their Independence And Confidence. Traditional Assistive Tools Such As White Canes And Guide Dogs Provide Only Limited Physical Guidance And Lack The Ability To Convey Real-time, Detailed Environmental Information. Existing Digital Solutions Often Focus On A Single Function, Require Multiple Devices, Or Depend Heavily On Internet Connectivity, Which Reduces Their Practicality And Reliability In Dynamic Surroundings.To Address These Limitations, The Proposed System Introduces An Integrated, AI-powered Assistive Technology That Combines Face Recognition, Obstacle Detection, And Currency Identification Into A Single, Compact, And User-friendly Device. The System Captures Real-time Visual Input Through A Wearable Or External Camera And Processes It Using Advanced Deep Learning Algorithms To Ensure High Accuracy And Rapid Response. YOLO Is Utilized For Obstacle Detection, Allowing The System To Identify And Track Nearby Objects, While The Grassmann Algorithm Supports Robust Face Recognition For Identifying Familiar Individuals. Additionally, A CNN-based Model Handles Currency Classification To Help Users Conduct Financial Transactions Independently. All Detected Information Is Converted Into Clear, Context-aware Audio Feedback, Guiding Users Safely And Effectively Through Their Environment. This Unified Approach Minimizes The Need For External Assistance, Enhances Personal Mobility, And Significantly Improves The Overall Quality Of Life For Visually Impaired Individuals. By Offering Affordability, Adaptability, And Precision, The Proposed System Stands As An Innovative Step Toward Intelligent Assistive Technology.

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Other Details

• Paper id:

  IJSARTV12I5105287

• Published in:

  Volume: 12 Issue: 5 May 2026

• Publication Date:

  2026-05-06

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