AI System for Smart Building Management
Smart building — not just automation. Resource optimization based on usage patterns, weather forecasts, and real-time data. Typical result: 20–35% reduction in resource consumption while improving comfort.
Subsystems and AI
HVAC Optimization: RL agent controls heating/cooling/ventilation. Input data: occupancy (CO2 sensors, Wi-Fi presence, cameras), weather forecast (OpenWeatherMap), building thermal characteristics, tariff grid.
Baseline → RL → 25–30% HVAC energy savings (validated across multiple projects).
Occupancy Prediction: LSTM/Prophet predicts room occupancy 24 hours ahead. Pre-conditioning 30–60 minutes before people arrive.
Lighting Control: Computer vision + presence sensors → dynamic lighting management. Daylight harvesting: natural light integration.
Elevator Optimization: ML on historical traffic patterns → predictive dispatching. 15–20% wait time reduction.
Anomaly Detection: Energy anomalies (leaks, malfunctions) → automatic alert to maintenance.
BAS Integration
BACnet/IP and Modbus — Building Automation Systems standards. AI layer integrates on top of existing BAS without infrastructure replacement.
Pipeline: 12–20 weeks
BAS audit → data collection → models → integration → commissioning. Significant time — calibration and tuning for specific building.