International Journal of Innovative Research in Computer and Communication Engineering

ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines

| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |


TITLE Agentic AI‑Powered Exam Proctor Assignment System
ABSTRACT An AI‑Driven Proctor Allocation System is proposed to streamline how professors are assigned as invigilators for university examinations. The work addresses persistent issues in manual planning, such as clashing schedules, uneven distribution of invigilation duties, and difficulty reacting to last‑minute staff unavailability. In the proposed architecture, Firebase serves as a centralized data store, while a Gemini‑based agentic AI module intelligently maps professors to classroom time slots using information from the Admin Module (departments, faculty records, classroom details, and exam schedules) and the Professor Module (personal timetables and declared availability). The system automatically generates conflict‑free duty rosters, detects and resolves overlaps, and updates allocations in real time; an Emergency Pool Module further supports continuity by suggesting suitable backup invigilators when a scheduled professor becomes unavailable. By combining centralised data management with AI‑driven decision making, the system aims to deliver a more efficient, accurate, and fair approach to proctor assignment in academic institutions.
AUTHOR GURURAJ T, ANIKET PATIL, POOJA V, SHALINI G, SOWMYA M S Department of Computer Science and Engineering, Bapuji Institute of Engineering and Technology, Davangere, Karnataka, India
VOLUME 177
DOI DOI: 10.15680/IJIRCCE.2025.1312029
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