Classroom Automation Using YOLO Algorithm

Abstract

In classrooms we have electrical devices left switched on, though students were not present in the room and this is a common occurrence in all our daily lives too. So, this becomes of utmost importance that this non-renewable form of energy being wasted is conserved as much as possible. So, in this project we use machine learning to automate the lights and fans in classrooms. In homes, classrooms and offices have electrical devices left switched on, though people were not present in the room and this is a common occurrence in all our daily lives too. So, this becomes of utmost importance that this non-renewable form of energy being wasted is conserved as much as possible. Many automation techniques are already proposed and implemented as well, but many among them are not completely related to electricity conservation and others are not very efficient. So, the proposed energy saving classroom automation system could be used to detect the presence of a person/student inside the classroom and automatically adjust the state of electrical appliances to reduce power consumption. This is done by implementing person detection using CNN (Convolutional Neural Network) with YOLO algorithm.