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Published Paper Details:
AI-Driven Women Safety Analytics: A Proactive Threat Detection System
Authors
PRERANA V RAO,KUSUMITHA P,SAMPADA VIKRANT KABULE,HIMANSU SEKHAR ROUT
Downlaod Center
Keywords
Sentiment analysis, partitioning dataset, parallel processing, combining results.
Abstract
Women's safety in public spaces should not calculate on
chance or introductory security styles traditional tools like
CCTV cameras and details generally respond after an incident
happens they do not stop problems from being these styles
constantly warrant the capability to predict risks in real time
this creates a big gap in safety plans that concentrate only on
replying as technologies like artificial intelligence machine
knowledge computer vision and the internet of goods
meliorate snappily were moving toward smarter security
systems these new systems can snappily spot possible troubles
notice unusual conduct and automatically start safety
procedures using these tools makes safety measures more
flexible and quick to respond they can advise police and other
askers right down indeed helping to avoid detriment before it
occurs this composition introduces the a powered women's
safety analytics system this system is designed to learn from
its surroundings understand gets patterns and take fast safety
conduct a pivotal part of this system is its capability to fete
gender through deep knowledge this helps descry strange
trends like a woman alone in a busy area or an unlooked-for
crowd forming which could gesture a safety concern the
system also uses special discovery styles like autoencoders
and one- class SVMs along with disguise estimation tools
analogous as open disguise and disguise net these tools
anatomize how people move and stand they can identify
movements that might mean someone is in trouble or feeling
uncomfortable allowing for quick help unlike aged systems
that need people to oversee them all the time this ai predicated system improves trouble discovery and waves up
contact with police it also has a new point gesture grounded
SOS signals sometimes women in pitfall can not press a fear
button or make a call the system can recognize specific
moves body signals or voice cues that show torture deep
knowledge algorithms trained to descry urgency in speech
can shoot cautions automatically indeed without physical
contact this provides a quick and hands-free way to call for
help the system also uses prophecy tools that anatomize
formerly crime data cover current situations and produce
heatmaps of risks this helps authorities see implicit troubles
before problems be insulation and fairness are truly
important particular data is kept safe with encryption and
the system is erected to avoid bias its thing is to meliorate
safety without violating individual rights or insulation.
IJCRT's Publication Details
Unique Identification Number - IJCRT2505246
Paper ID - 285388
Author type - Indian Author
Page Number(s) - c177-c186
Pubished in - Volume 13 | Issue 5 | May 2025
DOI (Digital Object Identifier) -
No Of Downloads - 92
Author Country - India, 560064, Bengaluru, Bengaluru, 560064, Science and Technology
Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882
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PRERANA V RAO,KUSUMITHA P,SAMPADA VIKRANT KABULE,HIMANSU SEKHAR ROUT, "AI-Driven Women Safety Analytics: A Proactive Threat Detection System", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 5, pp.c177-c186, May 2025, Available at :http://www.ijcrt.org/papers/IJCRT2505246.pdf
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