Monitoring System For Classroom Session In Skill Training Program

Abstract

Establishing successful learning experiences in contemporary educational settings requires the ability to track and comprehend student participation. Smart Lenz is an all-inclusive, artificial intelligence (AI)-powered classroom monitoring system that gives teachers real-time information about the behavior, emotions, and attentiveness of their students. In order to identify emotional states like happy, sorrow, rage, or surprise, Smart Lenz analyzes live video feeds from classroom cameras using state-of-the-art computer vision and deep learning algorithms. It also tracks facial landmarks and analyzes facial expressions.

This paper involves research study and survey to identify the influence of teachers' Voice on learners. Results from the study show that efficient lecture delivery helps students to improve their learning ability.

This research develops an intelligent Monitoring system (IMS) and this system typically utilizes various tools and technologies such as cameras, sensors and software application to observe student behaviors.

Convolutional neural networks (CNNs) are used for facial expression recognition, eye aspect ratio (EAR) and blink detection are used for attention tracking, and behavioral analysis is used to analyze posture and head movements. After being combined and presented, these data streams give teachers a dynamic perspective on classroom dynamics.

Algorithms:

• Face detection
• Landmark detection
• Emotion detection
• Attention tracking
• behavior Analysis.