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Scalable Automated Proctoring: Integrating Browser-Native Artificial Intelligence and Continuous Trust Evaluation Somnath Ghorpade; Prathamesh Bomble; Omkar Gargote; Vrushabh Chavan
Journal of Engineering and Scientific Research Vol. 8 No. 1 (2026)
Publisher : Faculty of Engineering, Universitas Lampung Jl. Soemantri Brojonegoro No.1 Bandar Lampung, Indonesia 35141

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jesr.v8i1.281

Abstract

Abstract—The ability of most insitutions to make an agreementswiftly to remote education highlighted numerous integrity issues,thus established the need for an application-wise authenticproctoring strategy. Nonetheless, present automated solution forproctoring is either based upon sophisticated deep convolutionalnetwork (such a deep YOLO network) time-consuming requiresgreat deal of computer power or constantly intrusive onlinedesktop application to integrate the knowledge from students notbeing located together with test location. Many of these approachdisqualify the students utilizing common computer parts theywere in all probability to use to even go on the web with, compromise the citizens of those pupils, two the ability to meddle withevidence acquired on a far more powerful proctoring solution.We propose a stream-lined, wholly virtual multi-modal AI basedProctoring system integrated to a Django platform (PostgreSQLserver for data storage) to get over those limitations. In thisproject, we demonstrated a system of make sure the proctoringsoftware unwilling run while offline onto a pupil computer. Thisproject we used the enormous computer-processing and memorylearning pipeline is similar to repacement by existing proctoringsystems with a lean angular multiplier modality spatially-tracersystem using Face–based facial recognitions of pupil to do GazeTraccing (em the result straight away) for objects detectionduring image minutely track for obiquitous objects on pupilview(s). Fourth, using all of those background sound analysisplus ongoing browser app up to a modern ”Trust Value”. Thetrust value will evaluate the behavior of student through out thewhole duration exam. This propose to features a way to designa proctoring system that utilizes minimal amount of bandwidthand computational resource, can be expanded to accomodatemany students taking a test simulteneously and comport toaccommodate with the student wellbeing- rather than likely makeany of these metrics deteriorate.Index Terms—Remote Proctoring, Uncertainty Estimation,Multi-Modal Fusion, YOLOv11, LSTM, Edge Computing.