Attendance monitoring is a mandatory requirement in educational institutions and organizations. Traditional attendance-marking methods are manual, time-consuming, error-prone, and vulnerable to proxy attendance. Although automated systems such as RFID, biometric fingerprint scanners, iris detection, and voice recognition exist, they often involve high costs, additional hardware, and maintenance complexity. This paper presents an Intelligent Attendance Monitoring System using Image ProcessingandArtificialIntelligence (AI) that leverages facial recognition technology for accurate and automated attendance marking. Since facial featuresserveas a primary biometric identifier for humans, face recognition offers a reliable and contactless solution. The proposed system uses a face recognition library to detect and recognize students from captured images and automatically records attendance in a database. Additionally, absentee notifications are sent to supervisors or parents via email. The system aims to provide high accuracy, reduced hardware cost, large data storage capability, and fast computation. Experimental evaluation demonstrates that the proposed system effectively minimizes manual effort, prevents fake attendance, and improves operational efficiency. Keywords: Face Recognition, Attendance Monitoring, Image Processing, Artificial Intelligence, Machine Learning, Automation