A Smart Energy Optimization Platform Powered by Discrete Mathematics
A unified platform that predicts, monitors, and optimizes campus electricity usage
using probability, graph theory, recurrence relations, and Boolean logic —
turning mathematical theory into real-world sustainability.
| Page | Name | Description |
|---|---|---|
| 1 | 🏠 Homepage (index.html) |
System overview, live stats, and quick navigation |
| 2 | 📊 Dashboard (dashboard.html) |
Central monitoring of energy metrics and alerts |
| 3 | 🏗️ Campus Layout (campus-layout.html) |
Graph visualization G=(V,E) for rooms and wiring |
| 4 | ⏰ Schedule Optimizer (schedules.html) |
Timetable integration and automation |
| 5 | 📈 Energy Analytics (analytics.html) |
Deep insights, forecasts, and historical trends |
| 6 | 💡 Device Control (devices.html) |
Manage devices, monitor power usage in real-time |
| 7 | 📄 Reports (reports.html) |
Generate and export optimization reports |
| Concept | Used For | Pages |
|---|---|---|
| Probability | Occupancy prediction, threshold optimization | 2, 4, 6, 7, 9 |
| Graph Theory | Campus wiring, sensor placement, connectivity | 3, 10 |
| Recurrence Relations | Energy trend forecasting, savings analysis | 1, 2, 5, 8 |
| Functions | Real-time readings and power calculations | 1, 2, 5, 6 |
| Boolean Logic | Automation and conditional rule systems | 4, 6, 7, 11 |
- Homepage
- Dashboard
- Campus Layout Manager
- Device Control Center
- Schedule Optimizer
- Probability Calculator
- Boolean Logic Editor
- Energy Analytics
- Graph Theory Tools
- Reports & Settings
- Admin Panel
- UI/UX Enhancements
| Layer | Technology |
|---|---|
| Frontend | HTML + CSS |
| Visualization | D3.js, Chart.js |
| Backend | Node.js + JS |
| Automation Logic | Boolean Rule Engine |
✅ Real-time energy monitoring
✅ Graph-based campus layout builder
✅ Smart scheduling and occupancy prediction
✅ Automated device control
✅ Bayesian probability simulations
✅ Minimum Spanning Tree (MST) optimization
✅ Visual logic editor with truth tables
✅ Customizable settings and API integrations
✅ Comprehensive reports and exports
✅ Admin-level analytics and performance insights
-
Energy Function:
f(r,t)→ Real-time energy consumption of room r at time t -
Savings Recurrence:
S_n = E_{n-1} - E_n→ Day-over-day energy improvement -
Occupancy Probability:
P_r(t) = Hours Occupied / Total Hours -
Graph Optimization:
MST via Prim’s / Kruskal’s
Dominating Set → Optimal sensor placement -
Automation Logic:
L_r(t) = O_r(t) ∧ C_r(t)→ Combined room and condition rule
Homepage → Dashboard → Campus Layout → Devices → Analytics → Tools → Settings/Admin
- AI-based anomaly detection
- Dynamic campus graph scaling
- Cloud sync & offline mode
- Voice-based device control
- Predictive maintenance alerts
This project not only reduces electricity waste but also builds a foundation for sustainable, AI-powered campuses.
It merges machine learning, optimization, and real-time systems into a single dashboard — bridging theoretical math with real-world utility.
⚙️ “Smart campuses aren’t built overnight — they’re modeled, optimized, and evolved through data.”