Smart & Sustainable University Resource Management System
Data-driven scheduling system (Java, JavaScript, MySQL) that models historical usage patterns to cut scheduling conflicts and improve facility utilisation.
Technologies
Engineering Focus
Engineered through the complete development lifecycle: requirements analysis, database normalization (3NF), modular service architecture, concurrency control, and systematic testing.
01. The Real-World Problem Space
University campuses struggle with classroom, lab, and facility allocation conflicts, leading to underutilized campus infrastructure and recurring scheduling overlaps.
02. Strategic Engineering Approach
Built a data-driven scheduling engine with a cross-functional team using Git-based version control and agile practice throughout the software engineering lifecycle.
System Architecture & Service Flow
Historical Campus Telemetry → Constraint Optimization Engine → Conflict Resolution Service → Dynamic Scheduling UI
Telemetry Ingestion
Captures department room requirements, student cohort sizes, equipment prerequisites, and instructor availability.
Historical Pattern Modeling
Analyzes historical utilization logs to predict congestion hotspots and idle intervals across campus facilities.
Automated Constraint Solver
Executes heuristic algorithms to assign spaces while guaranteeing zero instructor or classroom collision.
Interactive Faculty Portal
Provides department heads with real-time override abilities and analytics on sustainability and resource efficiency.
Technical Challenges Overcome
- •Balancing hard constraints (instructor availability, room capacity) with soft preferences across multiple departments.
- •Maintaining high responsiveness while computing permutations across hundreds of university classes.
Demonstrated Outcome & Verification
Awarded 1st Place at the SNPSU InnovEdge Ideathon 2026 for tangible campus impact and disciplined agile software execution.
Future Roadmap
Integrating IoT occupancy sensors to dynamically modulate campus lighting and climate control based on real-time room occupancy.