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Women Security Application Using Smart Emergency Response System and Real-Time Location Tracking

Authors:

Akash Kumar Sinha, Agashini V Kumar, Ratnadip Saha, Aishwarya Roy, Khushi Jayesh Kadel

Abstract- The increasing number of crimes against women, especially in urban and semi-urban regions, has raised serious concerns about personal safety and immediate access to help during emergencies. While numerous safety apps exist, many fall short in terms of usability, responsiveness, and real-time assistance. This paper presents the design and development of a mobile-based Women Security Application aimed at providing quick, reliable, and intelligent emergency support in threatening situations.

The core idea behind the application is to ensure that women in distress can seek help effortlessly, even when they are unable to manually operate their device. The system incorporates multiple modes of triggering SOS alerts, including shake detection and voice commands, allowing the user to initiate emergency responses discreetly. Once activated, the app sends the user's live location to pre-registered emergency contacts via SMS and push notifications, and continuously updates the location in real-time until the threat subsides. Additionally, the app operates in stealth mode to avoid drawing attention, offering a layer of protection in sensitive scenarios.

To further enhance safety, the application can be linked to a wearable device or smartwatch to monitor basic health vitals, automatically triggering alerts if abnormal readings are detected. The backend infrastructure is powered by Node.js and MongoDB, ensuring reliable data handling and seamless communication. Integration with APIs such as Google Maps enables efficient location tracking and alert delivery.

Through this project, we aim to bridge the gap between technology and real-world safety concerns, offering a practical and impactful solution tailored specifically to women’s needs.

Keywords— Women Safety, Emergency SOS, Real-Time GPS, Mobile Security Application, Shake Detection, Voice Command, Stealth Mode, Smartwatch Integration