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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM21530

Third Eye for the Visually Impaired Using Echolocation Technology

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM21530

Volume:

7 |

5 |

May 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

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

PPMT

Prof. Pravin M. Tambe

RK

Rajeshwari Khade

RS

Rutuja Shinde

AA

Aishwarya Ahire

NM

Nikita Murkute

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Abstract

The Third Eye is an innovative device that utilizes cutting-edge fields of study, such as computer vision, machine learning, embedded systems, and medical sciences, to assist individuals who are visually impaired in their daily lives. By incorporating artificial vision and deep learning technology into a wearable shield, blind individuals can walk freely and confidently, with the device detecting obstacles or other objects in their path and providing information via a speaker or headphones. To achieve this, we developed a convolutional neural network (CNN), a deep learning neural network-based object detection framework, that is programmed in Python and implemented on a Raspberry Pi processing unit. The CNN is capable of recognizing various objects, such as poles, and alerting the user via earphones that an object is in their path. This automated device is designed to be fast, affordable, and easily accessible to the visually impaired community. Our ultimate goal is to improve the lives of millions of blind individuals by providing them with a reliable and efficient technology that allows them to navigate the world with greater ease and independence

KEYWORDS

CNN Machine learning Deep learning Embedded System Object Detection

Cite This Article

Prof. Pravin M. Tambe, Rajeshwari Khade, Rutuja Shinde, Aishwarya Ahire, Nikita Murkute, "Third Eye for the Visually Impaired Using Echolocation Technology," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 5, May 2023. https://doi.org/10.55041/IJSREM21530

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Publication Date

5/26/2023

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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5

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

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