International Journal of Scientific Research and Engineering Development

Managing a college is, at its core, an information problem. The institution already knows which students are missing lectures, which ones are slipping in their internal marks, which ones have not submitted assignments in three weeks. The trouble is that this information sits in different places, managed by different people, in formats that were never designed to be combined. Coordinators who want a complete picture of how a student is doing have to collect pieces from multiple sources manually, which takes time they rarely have, and often happens too late for a useful intervention. We built the Smart Campus Intelligence System (SCIS) to close this gap. The system unifies five operational areas—the student academic lifecycle, institutional event management, examination administration, campus identity services, and placement support—on a single shared data layer. Three components use machine learning where simpler methods would genuinely underperform: a facerecognition attendance pipeline that removes the roll-call burden from faculty, a grade-trajectory model that surfaces at-risk students before end-semester marks are finalised, and a semantic job-matching engine that ranks candidates against position requirements based on meaning rather than term overlap.

Vinay Babannavar, Preetam Anil Kage,"Towards a Connected Campus: Design and Evaluation of an AI-Augmented Institutional Management Platform" International Journal of Scientific Research and Engineering Development, V9(3): Page(636-641) May-June 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.