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Nandepu Rama Venkata Durga Vamsi; A.Bhagyasri; Vattikuti Raghavendra; Sirigineedi Gamyasri; Sudhana Mukesh

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Authors: Nandepu Rama Venkata Durga Vamsi, A.Bhagyasri, Vattikuti Raghavendra, Sirigineedi Gamyasri, Sudhana Mukesh

Unique Paper ID: 174159
Volume: 11
Issue: 10
PageNo: 4178-4184

Keywords: No Keywords Found

Abstract:
This study introduces a real-time computer vision-based system for monitoring children's concentration levels during remote learning. Leveraging OpenCV and Mediapipe's Face Mesh for video capture and facial landmark detection, the system evaluates attention through visual cues such as eye movements, blink rates, and head posture. Lightweight machine learning models process these features to classify focus states, offering real-time feedback via a user-friendly Streamlit interface. Designed for affordability and accessibility, the system operates using standard webcams and computers, making it practical for home environments. By bridging a critical gap in remote education, this solution supports caregivers in enhancing children's study habits and ensuring sustained engagement.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 10
PageNo: 4178-4184

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Available:https://ijirt.org/article?manuscript=174159

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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