Securing Children Based On IoT And Emotion Prediction

Children’s safety is a major concern today. Child trafficking occurs frequently every day. This paper seeks to address parent’s concerns about the safety and security of their children. This model proposes three modules like finding the location of children through GPS, the second module is used to mark the attendance of children who are present inside the classroom using iBeacon, and the third module is used to predict children’s emotions through random forest algorithm. This paper gives a solution to find the location of children both by parents and teachers using the Android application and to take attendance as well as to identify the location of children inside the school campus by teachers. The mood states of the student, such as joy, sadness, fear, disgust, shock, anger, and neutrality, are automatically detected by the facial expression. This prediction will help the teacher to analyze in which subject the children are most interested. The main motive of this paper is to monitor the children wherever he/she goes and to predict the emotion. This system is developed using PIC microcontroller, GPS and iBeacon.