Rakshak: A Multi-Layered Intelligent Framework for Offline-Capable Proactive Emergency Response in Women’s Safety Systems

DOI

10.2991/978-94-6239-713-2_50How to use a DOI?

Keywords

Women’s Safety; Artificial Intelligence; Emergency Response; SOS Detection; Mobile Safety Application; Real-Time Monitoring; Multi-Trigger System; Smart Surveillance; Personal Security

Abstract

In today’s fast-paced society, women’s safety is still a major concern despite the tremendous improvements in technology. In addition to having a physical and psychological impact on victims, the rise in harassment, assault, and gender-based violence also imposes broader socioeconomic difficulties by limiting people’s freedom of movement and ability to engage in public life. While there are many safety applications available, the majority rely on manual activation techniques, like panic buttons, and need consistent internet access to work properly. Victims may not always be able to manually set off alarms in real-life emergencies, and network constraints in busy or remote locations further diminish the dependability of such systems in dire circumstances. These issues are addressed by the AI-powered mobile safety software Rakshak, which offers real-time support via a clever multi-triggered SOS mechanism. The system recognizes distress situations and automatically generates emergency warnings using AI-driven detection techniques like voice instructions, eye-blink patterns, and tap-based triggers. SponseTo ensure a quicker reaction time, Rakshak promptly notifies registered emergency contacts of the user’s location and sends alarm messages upon detection. With the goal of offering a dependable, self-sufficient, and intuitive safety solution for women in public areas, the proposed system aims to reduce reliance on manual intervention by incorporating a multi-trigger detection mechanism.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Suvarna Patil
AU  - Sneha Kanawade
AU  - Yashwant Karnawat
AU  - Karansinh Deshmukh
AU  - Siddhesh Chaudhari
AU  - Chinmay Karodpati
PY  - 2026
DA  - 2026/06/25
TI  - Rakshak: A Multi-Layered Intelligent Framework for Offline-Capable Proactive Emergency Response in Women’s Safety Systems
BT  - Proceedings of the International Conference on Advances in Computing Technology and Artificial Intelligence (COMPUTATIA 2026)
PB  - Atlantis Press
SP  - 673
EP  - 687
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6239-713-2_50
DO  - 10.2991/978-94-6239-713-2_50
ID  - Patil2026
ER  -