STUDY ON IOT BASED WOMEN SAFETY DEVICES WITH SCREAMING DETECTION AND VIDEO CAPTURING

Abstract

To propose an idea for implementing wearable IoT devices using the Raspberry Pi, which is equipped with a sound sensor, camera module, GPS, and GSM. When the sound sensor detects screaming, the SVM (support vector machine) algorithm in machine learning eliminates unnecessary noise and evaluates only the victim screaming. After assessing the victim's scream, the gadget promptly activates the camera module, which takes 30 seconds of footage. GPS will track the geographical coordinates and, using the GSM module, will send an alert message and an emergency call to the nearest police station. When the victim activates the switch in the second scenario, the camera module is immediately activated, and a 30-second clip is captured. The GPS will be active, and GSM will send an alert message with the status. The idea's major goal is to present a smart gadget for a woman that is entirely comfy and portable. When compared to other existing safety devices, the first and most crucial difference is the smart band's ability to shrink the size of gadgets.