International Journal of Science, Engineering and TechnologyAuthors: Rishabh Dubey, Saransh Kumar, Sanjana, Manpreet Singh
Abstract: Institutional security faces significant challenges in academic environments due to the logistical volatility of high-stakes examinations. This research developed an autonomous surveillance framework specifically designed for proctoring and premise security. The system utilized the YOLOv8 architecture for real-time detection, integrated with a Dynamic Identity Injection module to provision session-specific biometric datasets. This configuration allowed for contextually resetting authorization logic for every individual examination event. Spatio-temporal behavior analysis was facilitated to identify anomalies such as unauthorized item usage and suspicious gaze deviations. To enhance accountability, Vision-Language Models were integrated to generate natural language descriptions of flagged incidents for review by authorities. The architecture employed edge-centric processing and a rolling evidence cache to ensure compliance with the Digital Personal Data Protection Act. By combining probabilistic risk scoring with transient data management, this study provided a scalable and legally resilient solution for maintaining academic integrity in modern educational infrastructures. Experimental evaluation demonstrated a mean Average Precision of 0.92 at IoU 0.5, a processing latency of under 15 ms per frame at 30 FPS, and a 98.2% biometric validation accuracy, confirming the viability of the framework for real-world deployment.
DOI: http://doi.org/10.5281/zenodo.21716279
