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INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTS - IJCRT (IJCRT.ORG)

International Peer Reviewed & Refereed Journals, Open Access Journal

IJCRT Peer-Reviewed (Refereed) Journal as Per New UGC Rules.

ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013

Call For Paper - Volume 14 | Issue 3 | Month- March 2026

Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 7.97 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(CrossRef DOI)

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  Published Paper Details:

  Paper Title

Assessment and Exploring of Women's Safety using Machine Learning Techniques

  Authors

  Bhavana Sunil Jadhav,  Prof. Manisha Patil

  Keywords

: Natural Language Processing (NLP), Machine Learning (ML), Artificial Intelligence (AI), and Deep Learning

  Abstract


Nowadays, women face numerous challenges related to their safety; even in today's society, women's protection remains a challenge, despite significant technological advancements. Not all places guarantee women's safety, especially when they travel alone through desolate roads and abandoned areas. Emerging hand-held safety features for women require physical activity, such as pushing a button or shaking a machine, to activate the system after detecting a threat. We suggest alternatives that seek to resolve the shortcomings of current structures and provide women with false evidence of protection. We are building an IoT-based safety device with the help of the research framework. It works by forming partnerships with protection through a signature method of connected devices and alerting nearby family members and police stations when a woman is not safe. In addition, an explosion machine is also built for first-hand protection, which women may use to strike the attacker. The development design also incorporates additional functionality, such as the ability to submit community notifications and record voice messages. The development design includes a mobile app for women's protection, which displays safe places on the map based on the victim's current position, enabling them to access the secure place from their current location.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2501170

  Paper ID - 275358

  Page Number(s) - b467-b471

  Pubished in - Volume 13 | Issue 1 | January 2025

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Bhavana Sunil Jadhav,  Prof. Manisha Patil,   "Assessment and Exploring of Women's Safety using Machine Learning Techniques", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 1, pp.b467-b471, January 2025, Available at :http://www.ijcrt.org/papers/IJCRT2501170.pdf

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Call For Paper March 2026
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


ISSN
ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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