Publication

Abstract : In this modern era, women have shown excellence in all walks of life and stand equally with men in all sectors. So has increased violence against women due to this exposure. Hence, women security during travel is one of the critical issues faced by society, from the past and even today. The paper aims at providing a technological solution to this problem. For this, a system for forewarning and safeguarding the female cab users using machine learning is developed. An Android application is developed to collect data, and a virtual panic environment was created to collect the anomalies. The accelerometer data along the three coordinates was captured corresponding to normal and anomalies. Three machine learning models viz support vector machines, logistic regression, and Naïve Bayes are trained on data collected, and their test performance is compared in terms of accuracy. This trained model is further integrated with an Android application for real-time data collection and feedback.