Snoop : A Real-Time AI-Based Online Exam Invigilation Systems

Author(s)	Prof. Abha Pathak, Mr. Mahesh Sumb, Mr. Tanmay Shingote, Mr. Omkar Sawant, Mr. Shivam Kumar
Country	India
Abstract	Technology is growing day by day. We are seeing a rapid shift towards online education, and there are various platforms developed for online teaching. But there is no determined, structured product/application design to have a well-based exam system, i.e., no malicious activities happen. So, Snoop is an AI-integrated system designed to look at the students or people on their assessment test to be conducted by the educational platforms or the organizations for hiring candidates. The system designed for this activity has integration of various AI models for real-time detection for malicious activities. i.e., spoofing, unauthorized faces. It also gathers the valid sound that can occur during examination. This system working makes significant work in the online assessment by providing the secure, reliable and automated system
Keywords	Online Exam Monitoring, artificial intelligence (AI), Real Time Invigilation, Computer Visions, Auto anomaly detection, Automated Invigilation.
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 8, Issue 2, March-April 2026
Published On	2026-03-17
DOI	https://doi.org/10.36948/ijfmr.2026.v08i02.68370

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