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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM48200

Nari Rakshak: An AI-Driven Application for Women's Safety

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM48200

Volume:

9 |

5 |

May 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM48200

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

HG

Himanshi Gupta1

AS

Agrima Srivastava2

KB

Kanishka Bhardwaj3

DT

Dr.Pooja Tripathi4

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Abstract

Women’s safety is a major concern in today’s world, with rising cases of violence making it essential to have tools that help women feel secure and protected. Nari Rakshak is an AI-driven solution designed to provide real-time support in dangerous situations, giving women an extra layer of security when they need it most.This paper takes a closer look at how Nari Rakshak works, the technology behind it, and how it compares to existing safety apps. While many apps already offer features like SOS alerts and location tracking, they often fall short in critical moments. Our solution goes a step further by integrating panic audio recording, AI-based analytics, and smart emergency response to ensure faster and more effective assistance.Beyond just analyzing current apps, we also explore what makes a truly reliable women’s safety tool and where future innovations can take this technology. The goal is simple—to create a trusted companion that not only helps women stay safe but also gives them confidence in their daily lives.

KEYWORDS

Women’s Safety AI Technology Emergency Support Smart Security Future Innovations.

Cite This Article

Himanshi Gupta1, Agrima Srivastava2, Kanishka Bhardwaj3, Dr.Pooja Tripathi4, "Nari Rakshak: An AI-Driven Application for Women's Safety," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 5, May 2025. https://doi.org/10.55041/IJSREM48200

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Publication Date

5/17/2025

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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0

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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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No funding information available for this research.

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