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Intelligent invigilator system based on target detection.

Jing Xue¹, Wen Wu¹, Qingkai Cheng¹

¹School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, China.

Multimedia Tools and Applications

|June 26, 2023

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This study introduces an intelligent remote invigilation system using EfficientDet and centroid tracking to detect cheating during online exams. The system achieves high accuracy in identifying suspicious behaviors and uses audio analysis for further evidence.

Area of Science:

Computer Science
Artificial Intelligence
Educational Technology

Background:

The COVID-19 pandemic necessitated a shift to online remote invigilation for academic examinations and recruitment interviews.
This transition increased opportunities for academic dishonesty and cheating.
Existing remote invigilation methods lack robust mechanisms for detecting fraudulent activities.

Purpose of the Study:

To develop an intelligent invigilation system capable of detecting and preventing cheating in online remote testing environments.
To enhance the integrity and reliability of online assessments.
To provide a comprehensive solution combining visual and auditory analysis for cheating detection.

Main Methods:

Utilized the EfficientDet target detection network model for visual analysis of examinee behavior.

Keywords:

Abnormal behavior detection Audio analysis Centroid tracking EfficientDet Intelligent invigilation

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Integrated a centroid tracking algorithm for continuous monitoring and tracking of individuals.

Developed an auxiliary audio detection module to analyze environmental sounds for suspicious activities.

Main Results:

The EfficientDet network achieved an average detection accuracy of 81% for target detection.
The proposed cheating behavior detection model demonstrated effective detection, tracking, and recognition in remote testing scenarios.
Real-world experiments with online test videos showed a cheating behavior detection accuracy of 83.1%.

Conclusions:

The intelligent invigilation system effectively addresses the challenges of cheating in online remote assessments.
The combination of EfficientDet visual detection and audio analysis provides a robust and reliable method for ensuring academic integrity.
The system offers a practical solution for universities and enterprises conducting secure online examinations and interviews.