Smart Attendance and Behavioural Analysis
Praneeth1, Naresh2, Sai Kiran3, Anvesh4, Deepak5
Under the guidance of Mr.K.Y.Vamsi Naidu(Asst. Professor)
Department of Computer Science and Engineering(AI & ML),Raghu Institute of Technology
Abstract: This project introduces the Smart Attendance and Behavioural Analytic System, designed to enhance student engagement and learning outcomes in modern educational environments. Utilizing advanced voice recognition technology, the system automates attendance marking, allowing students to check in simply by stating their name or a designated phrase.
This automation significantly reduces the time and effort required for manual attendance procedures. The system incorporates Natural Language Processing (NLP) and Machine Learning (ML) techniques to analyze students' vocal expressions, tone, and speech patterns, providing real-time insights into their emotional and engagement states during classes, such as attentiveness, confusion, and interest. Equipped with a user-friendly dashboard, educators can effortlessly track attendance, visualize engagement metrics, and identify behavioural patterns over time.
Equipped with a user-friendly dashboard, educators can effortlessly track attendance, visualize engagement metrics, and identify behavioral patterns over time. The system also issues alerts for drops in student engagement or persistent absenteeism, facilitating timely interventions. By integrating with Learning Management Systems (LMS), it streamlines attendance reporting and behavioural analysis, allowing institutions to monitor and support students effectively. The system also issues alerts for drops in student engagement or persistent absenteeism, facilitating timely interventions. By integrating with Learning Management Systems (LMS), it streamlines attendance reporting and behavioral analysis, allowing institutions to monitor and support students effectively.
