IoT and AI Assisted Automated Attendance Marking System Using Yolo Facial Recognition

In today’s fast-paced educational and corporate environments, managing attendance efficiently hasbecome a critical task. Traditional methods of attendance marking, which often rely on manual input orrudimentary tracking systems, can be time-consuming, error-prone, and susceptible to fraud. Asinstitutions and organizations seek to streamline their operations and enhance productivity, there is agrowing demand for innovative solutions that offer greater accuracy and ease of use. Automatedattendance marking using Artificial Intelligence (AI) represents a significant leap forward in this regard.This paper proposes an automated attendance marking system using facial recognition which isimplemented by the state-of-the art object detection model YOLOv8. The trained model is deployed in anIoT framework with Raspberry Pi hardware to identify the faces and mark attendance in an excel sheet.This will be shared to the concerned incharge via Internet. Based on the experimentation, the proposedsystem performance is robust and reliable to any working environment.