SafeHerChild AI: An AI Powered Real Time Child and Women Abuse and Violence Detection System Using Deep Learning, Computer Vision, and Generative AI with Automated Alert Notifications

June 2026
Vol-12, Issue-3
Paper ID: 28605
ISSN: 2395-4396
Downloads: 0

Abstract & Details

Research Area
Computer Science and Engineering
Keywords
Deep Learning Computer Vision CNN OpenCV Violence Detection Generative AI Flask Behavioral Analytics Safeguarding Intelligence Automated Alert Notifications Women Safety Child Protection Real Time Detection Abuse Recognition
Abstract
SafeHerChild AI is an intelligent safeguarding framework designed for Real Time child and women abuse detection through the integration of Deep Learning, Computer Vision and Artificial Intelligence technologies. The system analyzes visual information to identify violence manifestations, aggression signatures and potential victimization scenarios with high predictive reliability. Advanced behavioral interpretation mechanisms facilitate autonomous threat recognition while automated alert notifications support rapid protective intervention. The framework incorporates a Detection Page for analytical processing, a Dashboard for safeguarding intelligence management, a Knowledge Center for awareness dissemination and an About module for system transparency. SafeHerChild AI enhances situational awareness, strengthens humanitarian protection and contributes toward technologically empowered safeguarding ecosystems.

Author Information

# Name Institute / Affiliation
1 Arti Humnabade Visvesvaraya technological university, belagavi
2 P Sripalreddy Visvesvaraya technological university, belagavi

How to Cite

Use the following formats to cite this article in your research.

APA Style
Humnabade, Arti & Sripalreddy, P (2026). SafeHerChild AI: An AI Powered Real Time Child and Women Abuse and Violence Detection System Using Deep Learning, Computer Vision, and Generative AI with Automated Alert Notifications. International Journal of Advance Research and Innovative Ideas In Education, 12(3), 1995-1998.
MLA Style
Humnabade, Arti, and P Sripalreddy. "SafeHerChild AI: An AI Powered Real Time Child and Women Abuse and Violence Detection System Using Deep Learning, Computer Vision, and Generative AI with Automated Alert Notifications." International Journal of Advance Research and Innovative Ideas In Education, vol. 12, no. 3, 2026, pp. 1995-1998.
IEEE Style
Arti Humnabade and P Sripalreddy, "SafeHerChild AI: An AI Powered Real Time Child and Women Abuse and Violence Detection System Using Deep Learning, Computer Vision, and Generative AI with Automated Alert Notifications," International Journal of Advance Research and Innovative Ideas In Education, vol. 12, no. 3, pp. 1995-1998, 2026.
Vancouver Style
Humnabade Arti, Sripalreddy P. SafeHerChild AI: An AI Powered Real Time Child and Women Abuse and Violence Detection System Using Deep Learning, Computer Vision, and Generative AI with Automated Alert Notifications. International Journal of Advance Research and Innovative Ideas In Education. 2026;12(3):1995-1998.
Harvard Style
Humnabade, Arti & Sripalreddy, P (2026) 'SafeHerChild AI: An AI Powered Real Time Child and Women Abuse and Violence Detection System Using Deep Learning, Computer Vision, and Generative AI with Automated Alert Notifications', International Journal of Advance Research and Innovative Ideas In Education, 12(3), pp. 1995-1998.
Chicago Style
Humnabade, Arti and P Sripalreddy. "SafeHerChild AI: An AI Powered Real Time Child and Women Abuse and Violence Detection System Using Deep Learning, Computer Vision, and Generative AI with Automated Alert Notifications." International Journal of Advance Research and Innovative Ideas In Education 12, no. 3 (2026): 1995-1998.
Turabian Style
Humnabade, Arti and P Sripalreddy. "SafeHerChild AI: An AI Powered Real Time Child and Women Abuse and Violence Detection System Using Deep Learning, Computer Vision, and Generative AI with Automated Alert Notifications." International Journal of Advance Research and Innovative Ideas In Education 12, no. 3 (2026): 1995-1998.

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