Women Safety Analytics –Protecting Women from Safety Threats
DOI:
https://doi.org/10.47392/IRJAEH.2025.0431Keywords:
Women Safety, Real-time Analytics, Emergency Response, Android Application, Java Backend, XML, UI, Location Sharing, Gesture-based Alerts, Audio Trigger, Machine Learning, Intelligent Sensing, Risk Detection, Video/Image Analytics, Mobile Security, Contextual Risk Analysis, Safety Monitoring, Proactive Alert System, Emergency Contacts, Smart Technology Integration, Public SafetyAbstract
Women Safety Analytics – Safeguarding Women against Safety Risks is an end-to-end mobile application that ensures women's safety through real-time analytics, intelligent sensing, and machine learning. Built on Android Studio with Java for backend services and XML drag-and-drop for the user interface, the application offers a simple and effective platform for emergency response. Major features of the application are user registration and login, an emergency button that, upon press, directly shares the user's current location with pre-registered emergency contacts. The app also offers gesture-based alerts like a phone shake—to discreetly initiate location sharing. It also offers an audio trigger: upon detection of the word "Help" via the microphone, an alert is sent to the emergency contacts. The second part of the project uses machine learning to identify potential safety risks in public observation settings. In particular, the system can detect situations where a woman is single in a potentially risky environment and automatically raise alerts. This proactive capability utilizes image or video analytics to determine contextual risk and initiate timely response.By integrating mobile technology with smart analytics, this project seeks to deliver a complete solution to forestall and react to safety risks against women, ultimately to contribute to a more secure and safer environment.
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Copyright (c) 2025 International Research Journal on Advanced Engineering Hub (IRJAEH)

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