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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM46938

Vision sense: Object Detection and Navigation Aid for the Visually Impaired

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM46938

Volume:

9 |

5 |

May 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM46938

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

SPR

Sama Premanand Reddy

CSK

Chenna Sravan Kumar

DKNS

Dr. Kamal Nain Sharma

DPK

Donthikurthi Pradeep Kumar

NLSR

Neelam Lokesh Sai Raja

NKU

Nikhilesh Kumar Upadhyay

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Abstract

living in a world without vision is fraught with many challenges that sighted people take for granted. For the visually impaired, even mundane activities like walking through crowded areas, detecting obstacles, or identifying objects can be intimidating and even hazardous. Important views are like white canes and training dogs, and information provision limitations. With recent changes in computer vision and machine learning, there is an increasing chance to create smart systems that can improve accessibility to blind people. VisionSense is a new object detection and navigation system’s goal is to overcome these challenges by combining computer vision technologies. By using real-time image processing and deep learning based object detection algorithms, VisionSense is able to detect and inform the user about the presence and location of objects within their surroundings. Coupled with initiative audio or haptic feedback mechanisms, the system enables users to make informed navigation choices and steer clear of possible dangers. This work describes the design, development of Vision Sense, emphasizing its capability to greatly enhance the quality of life for the visually impaired. The system is not just affordable and light weight but also flexible to indoor and outdoor spaces, making it a viable remedy for accessible, real-time wayfinding aids.

KEYWORDS

Python Flask OpenCV YOLO (YOU ONLY LOOK ONCE) v8 HTML CSS Java stack Bootstrap ML(MACHINE LEARNING).

Cite This Article

Sama Premanand Reddy, Chenna Sravan Kumar, Dr. Kamal Nain Sharma, Donthikurthi Pradeep Kumar, Neelam Lokesh Sai Raja, Nikhilesh Kumar Upadhyay, "Vision sense: Object Detection and Navigation Aid for the Visually Impaired," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 5, May 2025. https://doi.org/10.55041/IJSREM46938

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Publication Date

6/4/2025

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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