In order to ensure that everyday activities run smoothly, attendance management is a critical activity in educational institutions. Traditional attendance management systems frequently rely on labor-intensive, error-prone, and resource-intensive manual methods. Automation and process streamlining of attendance management procedures have recently been made possible by the combination of Internet of Things (IoT) and Artificial Intelligence (AI) technology. Utilizing the synergies between IoT and AI, this study provides a creative strategy to improve attendance management in educational institutions. The suggested system collects real-time attendance data from students and staff members using IoT-enabled devices such biometric sensors, smart cards, and facial recognition cameras. The institute's doors, common areas, and classrooms all have these devices carefully placed there. Following collection, AI algorithms and techniques are used to process and analyze the attendance data. The use of machine learning algorithms ensures reliable identification and lowers the danger of fraudulent operations by detecting and recognizing people' distinctive identifiers, such as fingerprints, facial features, or RFID tags. Facial recognition is done with the use of deep learning models, making attendance tracking effective and unobtrusive.