Surveillance based Child Kidnap Detection and Prevention Assistance

Abstract

This research paper is based on child kidnap detection and prevention to identify susceptible child kidnap by unauthorized persons. The intelligent surveillance system proposed for this is known as "AICare". The purpose behind developing a proper kidnap detection methodology is to enhance and strengthen the existing child security systems. The key is to identify the main characteristics of a kidnapper in real-time, which follows face recognition, speed detection and object detection theories. Face recognition is used to identify whether the outlined individual has covered his body, especially his face, to hide the true identity, or else the person's face is directly processed for authentication. Speed detection is helpful in calculating movement speed and capturing whether the targeted individual is moving in a hurry. Finally, the stranger is subjected to object detection in order to classify whether he/she is handling a sharp object or not. The captured outcomes are subjected to a decision tree to resolve the person as a kidnapper suspect. The system results in an overall accuracy that is above 90%. As this solution is child-sensitive and responsive, it provides a long term platform that can real-time monitor for potential kidnap based on the kidnapper characteristics to support the working from home parents to take care of their children during crucial times.