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In the present world, women harassment and its associated threatening are increasing day-by-day on several places. Specifically, the social mediums are the major reason of such things happening in global manner. The person sitting in front of system can do anything without mentioning any identities, so that it is easy for threatening and do unwanted illegal activities accordingly. The basic motto of this paper is to design a new methodology to provide a safety mechanism to women to prevent themselves from harmful persons. In this paper a new methodology is introduced, which is called as Machine Learning based Social Threatening Filter (MLSTF). This proposed approach identifies the threats raised against women in Social Medias such as FaceBook, Twitter and so on. The logic of machine learning is associated with the proposed approach to identify the tweets raised in social media sites, manage that as a dataset for identifying the harmful contents and find out the word intensities to recognize the contents presented in it. This paper also provides a way to collect the real-time data from the women by means of placing the Smart Wearable Device (SWD) on respective person end to monitor the details instantly. This device contains several intelligent sensor units such as Body Position Identifier, Location, Accident Detection Sensor, Small Mic for recognize the emergency voice to act like a black-box and the pen hole camera for capturing the respective place picture. These all sensors are integrated together into the SWD to monitor the real-time women data and pass such data to the server end for processing by using Internet of Things (IoT …