WOMEN SAFETY AND HEALTH MONITORING DEVICE USING IOT

Abstract

Safety and health monitoring have emerged as critical global challenges for women in view of the increasing incidence of harassment, assault, kidnapping, and sudden medical emergencies, especially under conditions where victims cannot trigger the safety mechanism manually. Various solutions exist, including mobile applications, SOS buttons, and GPS-based tracking; most of them rely on user intervention and use Internet connectivity, which makes them quite useless during high-risk or incapacitating situations [3], [4], [7]. Though a number of wearable devices and IoT-based systems have been proposed in the last few years, many of these are still based on manual triggers or an intelligent decision-making system is lacking [9], [15], [20].

The proposed IoT-based Women Safety and Health Monitoring Device aims at autonomous processing with real-time detection and response in case of an emergency. The presented system is developed using a Raspberry Pi integrated with multiple sensors such as pulse and SpO₂, body temperature, accelerometer–gyroscope, microphone, GPS, GSM, and camera module for continuous monitoring of physiological and environmental parameters [8], [16], [17]. These multi-sensor data are analyzed using machine learning techniques to classify normal and abnormal conditions. This enhances the detection accuracy and reduces false alarms arising from a threshold-based approach [2], [6], [28]. Upon detection of abnormal health parameters, sudden violent movements, or panic-related audio cues, the system automatically triggers a multi-level emergency response. In this regard, SMS alerts bearing real-time GPS coordinates are transmitted via GSM, images are captured for situational evidence, and an audible alarm is activated to attract nearby attention, all ensuring reliable operation in the absence of internet connectivity [5], [18], [30]. The inclusion of offline communication and autonomous activation also directly addresses the shortcomings of previous women safety systems reported in [11] and [25].

The proposed system ensures greater reliability compared to existing approaches in the literature by minimizing reliance on manual activation, introducing intelligent sensor fusion, and thereby supporting continuous health monitoring with personal safety [12], [21], [23]. The device will be compact, economical, and deployable in real-world settings. The system can also be easily expanded for supporting elderly people, children, and other vulnerable groups, moving toward developing proactive and intelligent personal safety [14], [26], [27].