IOT- BASED WOMEN SECURITY SYSTEM

Abstract

The safety of women in public places, workplaces, and while travelling remains a serious social concern. Incidents of harassment, stalking, and assault often take place in situations where the victim cannot reach a phone, unlock it, and dial for help in time. Even when a call is made, the person receiving it may not know the exact location of the victim. This paper presents an IoT-based women security system in the form of a small wearable device that can raise an emergency alert with a single action and share the live location of the wearer with trusted contacts and the nearest police control room. The device is built around an ESP32 microcontroller connected to a GPS receiver, a GSM module, a pulse sensor, a three-axis accelerometer, a small microphone, and a concealed push button. When the button is pressed, or when the device detects a combination of an abnormally high heart rate and sudden violent movement, it enters the emergency mode. In this mode it obtains the current coordinates from the GPS receiver and sends SMS messages containing a map link to preconfigured contacts. At the same time it places an automatic voice call to the first contact so that someone is alerted even if messages are not read immediately. Where Wi-Fi or mobile data is available, the device also publishes its location and sensor readings to a cloud platform using the MQTT protocol. A companion mobile application and a web dashboard display the live track of the wearer, the time of the alert, and the recorded audio clip captured by the microphone during the first seconds of the emergency. The location is updated every few seconds until the alert is cancelled by the wearer with a secret button sequence or closed by a responder, so that contacts can follow the movement of the victim if she is being taken away. The system also includes deterrent features. A loud buzzer can be activated to attract the attention of people nearby, and an optional shock circuit provides a means of selfdefence. A fake call feature on the mobile application allows the user to leave an uncomfortable situation without confrontation. All alerts are logged in the cloud with time, place, and sensor data, which can later assist police investigation and help authorities identify locations where incidents occur repeatedly.