An Automated Women Safety Framework Using Machine Learning and Real-Time Risk Assessment

K. Vishnu Vardhan; K. Venkata Ramana; T. Sravan Kumar; V. Chandra Shekar; Rabiya Begum

doi:10.64643/ijirtv12i10-195308-459

March 30, 2026International Journal of Innovative Research in TechnologyOpen Access

An Automated Women Safety Framework Using Machine Learning and Real-Time Risk Assessment

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Key Points

The aim is to assess how machine learning can enhance safety measures for women through real-time risk assessments.
Developed an automated framework incorporating machine learning techniques.
Evaluated real-time risk assessment features.
Assessed safety framework effectiveness through simulations.
The framework shows potential for real-time risk identification.
Participants reported increased awareness of safety issues.
Enhanced safety interventions were noted in simulated environments.

Implication

Evaluates a safety framework that uses machine learning to assess risks for women, suggesting improvements in safety measures.

Abstract

Explore the article titled An Automated Women Safety Framework Using Machine Learning and Real-Time Risk Assessment from IJIRT Volume 12, Issue 10. This study evaluates the effectiveness of teaching programs on waste management knowledge among women.

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Cite This Study

Vardhan et al. (2026) studied this question.

synapsesocial.com/papers/69eb0a66553a5433e34b4753 https://doi.org/10.64643/ijirtv12i10-195308-459

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An Automated Women Safety Framework Using Machine Learning and Real-Time Risk Assessment

Key Points

Implication

Abstract

Discussion

Cite This Study

An Automated Women Safety Framework Using Machine Learning and Real-Time Risk Assessment

Key Points

Implication

Abstract

Discussion

Cite This Study

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