Smart Safety and Security Solution for Women using kNN Algorithm and IoT

In the global scenario, women’s safety is a crucial problem. The security of women has become a greater challenge to many families in their daily life, hence a system is developed using rapidly growing technologies to address this problem. This paper mainly focuses on an IoT based self-security system that is comfortable, easy to use and wearable, and helps to share the user location when they feel panic and also help to find the nearest safe place. The designed system is user friendly and it can be accessed only by a specific person. The system is controlled through raspberry pi, and it has two different modes namely normal mode and security mode. In normal mode, user can register their fingerprint, and in security mode, the fingerprint sensor acts as a panic button, and when a fingerprint is detected system shares the location and captures the photo of the culprit and stores it in the cloud. The machine learning algorithm gets the user location as input and predicts the nearest safe place location.