AI Exam Proctoring System

Online examinations and virtual interviews face major challenges in maintaining fairness, preventing cheating, and ensuring candidate attention without physical supervision. To address these issues, an AI Exam Proctoring System is developed as an intelligent monitoring solution that uses webcam and microphone inputs to observe student behavior in real time. The system applies Computer Vision and Artificial Intelligence techniques to detect face presence, eye movement, head direction, screen focus, and suspicious activities such as looking away frequently, multiple person presence, and unusual movements. It also uses audio analysis to identify background noise, talking, or external disturbances during the examination. The application continuously monitors candidate behavior, generates alerts for rule violations, and provides a final integrity report based on focus level and suspicious events. Additionally, the system helps institutions and organizations conduct secure, transparent, and automated online assessments with reduced manual invigilation effort. The results show improved monitoring accuracy, enhanced exam security, and efficient remote assessment management.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-16
DOI
https://doi.org/10.5281/zenodo.20716958
Primary Topic
Intelligent Tutoring Systems and Adaptive Learning
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI Exam Proctoring System

Monica M, Gayathri N
Zenodo (CERN European Organization for Nuclear Research)
Intelligent Tutoring Systems and Adaptive Learning
article

AI Exam Proctoring System

Monica M, Gayathri N
article en

Abstract

Online examinations and virtual interviews face major challenges in maintaining fairness, preventing cheating, and ensuring candidate attention without physical supervision. To address these issues, an AI Exam Proctoring System is developed as an intelligent monitoring solution that uses webcam and microphone inputs to observe student behavior in real time. The system applies Computer Vision and Artificial Intelligence techniques to detect face presence, eye movement, head direction, screen focus, and suspicious activities such as looking away frequently, multiple person presence, and unusual movements. It also uses audio analysis to identify background noise, talking, or external disturbances during the examination. The application continuously monitors candidate behavior, generates alerts for rule violations, and provides a final integrity report based on focus level and suspicious events. Additionally, the system helps institutions and organizations conduct secure, transparent, and automated online assessments with reduced manual invigilation effort. The results show improved monitoring accuracy, enhanced exam security, and efficient remote assessment management.

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Openalex Percentile: Top 4%
Intelligent Tutoring Systems and Adaptive Learning
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.