Designing and Implementing a System for Automation of Lab using IoT and Computer Vision

Abstract

Face recognition attendance system is a tool for recognizing the faces while taking attendance by using face biometrics based on monitor camera image capturing. In the smart attendance system, a raspberry pi system will be able to find and recognize human faces. The proposed system is based on face recognition to maintain the attendance record. The recognized students are marked as present and their attendance is updated with corresponding student name, date & time.
Recently computer vision focused on building systems for observing humans and understanding their look, activities, and behavior providing advanced interfaces for interacting with humans, and creating models for various purposes. To function the system, they require methods for detecting people from a given input image or a video. To detect the moving human body from the background image in video sequences for human body tracking for automation of the lab. It involves the control and automation of the lights, fan and electricity supply to the computers. The main purpose is to make the lab automated with the help of Raspberry Pi.
This paper presents an algorithm for detecting moving objects based on background subtraction where the moving humans are accurately and reliably detected. This will help to reduce the cost, electricity consumption which are high & to get rid of unnecessary usage of the electricity. The proposed method runs rapidly, exactly and fits for the concurrent detection of humans and recognizing their face. Such a system would have the capability to provide secure monitoring of laboratories.