Building Energy Optimization AI
Impact23% energy savings
Energy Savings23%
Buildings50+
Annual Savings$1.2M
Overview
Built an AI-powered energy optimization system for a property management company to reduce energy costs across their commercial building portfolio. The system predicts optimal HVAC settings based on occupancy, weather, and usage patterns.
The Challenge
Energy costs were a major expense across the building portfolio, with HVAC systems often running inefficiently based on fixed schedules.
The Solution
Deployed reinforcement learning models that learn optimal control strategies for each building, combined with occupancy prediction and weather forecasting. Integrated with existing BMS systems via BACnet.
Key Results
23% reduction in energy consumption
Deployed across 50+ buildings
$1.2M annual savings in energy costs
Tech Stack
PythonTensorFlowRay RLlibTimescaleDBGrafanaBACnetAzure IoT Hub