Based on the results, the average time needed to share locations is 0.91 seconds, and the average time needed to capture is 11.57 seconds, if the device and receiving cellphone use the same network. It uses the Raspberry Pi Zero W controller, the GNSS HMC5983 SAW LNA GPS Module to determine the location, and the 5MP Raspberry Pi Zero Camera Module to capture the incident. Thus, in this research a safety device that can be held by children is designed and is equipped with a button that can be pressed, then it will automatically send the location and photo of the scene to the parent's cellphone via the telegram application. Various safety devices that are commonly known as smart wearable devices have been created, but they still have many shortcomings. The world needs to pay attention to children who often become victims of violence and cannot escape social problems. The results of experimentations proved to be really promising with an accuracy of 94.7%. If an emergency situation is triggered, a GSM/GPS module will generate emergency in case of after-shock otherwise will warn the female device bearer. There is a situation-based analysis for relative modelling based on face recognition as well as fuzzy labeling of verbal conversations. Hidden Markov Models (HMM) offer scope for better predictive analysis for its dynamic probabilistic nature and helped us developing a dense sensing approach based on traces of suspicious activities. Internet of Things (IOT) based platform provides dexterity and dynamicity in correlating a plethora of sensors and actuators to ensure women safety. This paper proposes a concept of a multivariate security paradigm for women under possible offensive threats by deep sensing approaches. Several nefarious approaches to women that outraged the entire nation awakened the scientists globally to design smart apps for women safety. Smart technologies for women safety are gaining popularity over the last few decades.
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