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Published Date: 03-04-2025

Smart Guiding Glasses for Visually Impaired People in Indoor Environments Using Machine Learning

This projectdiscusses innovative development of intelligent guiding glasses designed to help visually disabled individuals sail into closed environments. Using auto - learning technologies, these glasses aim to boost mobility and independence for users, providing real - time help and prevent detection .

Key features

  • Detension of Hurdles: Using advanced computer - vision algorithms, glasses may identify obstacles in the user's way by warning them through audio or space response.

  • Help for the Sea: Integration of Systems GPS and home positioning allow for accurate navigation within complex areas within the home, such as shopping centers or airports .

  • Object Agreement: Car learning models may recognize common objects by helping users identify objects or reference points around them .

  • Sound Commands: Users can interact with glasses using voice commands, making it easier to search for information or change arrangements without having to use their hands.

  • Customize User: The system can learn from user preferences and habits, adapting its answers and vigilance to adapt to individual needs.

  • Private Data: Protecting user data is key; the system will include powerful security measures to store personal information .

These clever guiding glasses present an important step forward in assisting technology, aiming to empower individuals with visual problems, improving navigation and interaction with closed environments.


We have more details like Algorithm Information, Condition Checks, Technology, Industry & Human Benefits:


1. Title Page

  • Title Sources

2. Abstract

  • Summary of the Project
  • Key Findings
  • Keywords

3. Introduction

  • Background
  • Problem Statement
  • Research Questions
  • Objectives

4. Literature Review

  • Theoretical Framework
  • Review of Related Studies
  • Gaps in the Literature

5. Project Methodology

  • Research Design
  • Data Collection Methods
  • Data Analysis Techniques
  • Ethical Considerations

6. Project Results

  • Data Presentation
  • Statistical Analysis
  • Key Findings

7. Discussion

  • Interpretation of Results
  • Implications of Findings
  • Limitations

8. project Conclusion

  • Summary of Findings
  • Recommendations
  • Future Research Directions

9. References

  • References and Resources Links

10. Appendices

  • Final Source Code
  • Survey
  • Live environment/Real world Data Sets 
  • Additional Figures and Tables


The final table of contents depends on the project selection.


Project Delivery Kit


Project Source Code

Installation Guide

Data Sets and Samples

Usage Terms

Deployment Guide & More

Frequetly Asked Questions






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