Results Case study

AI Occupancy Based HVAC Controls results

CSUN Lilac Hall: 28% less electricity, 64% less natural gas, with software alone.

Brick and concrete university building with an entrance stairway
Illustrative image

AI Occupancy Based HVAC Controls results

Measured before and after at Lilac Hall.

  • 28% less electricity
  • 64% less natural gas
  • 3-month payback
  • About 26 metric tons of CO2e avoided per year

All figures are AI Occupancy Based HVAC Controls results from KenergyAI's own before-and-after metered data.

The building

Lilac Hall is a 10,000 sq ft faculty office and collaborative workspace building at California State University, Northridge, built in 2018. KenergyAI manages about 8,000 sq ft. It already had networked lighting controls, a BACnet BMS and VAV boxes.

The problem

Traditional schedules still conditioned empty rooms for hours every day.

What we did

We installed KenergyAI AI Occupancy Based HVAC Controls on a university virtual machine linked to the existing BACnet network. No new sensors, no construction, no changes to BMS sequences. KenergyAI reads occupancy from the lighting controls and adjusts setpoints only when spaces are empty. The existing BMS stays in control when spaces are occupied.

How it was measured

Sep 2023 to May 2024 (before) vs. Sep 2025 to May 2026 (with KenergyAI).

MeasureBeforeWith KenergyAIChange
Electricity62,106 kWh44,847 kWh28% less
Natural gas6,594 therms2,390 therms64% less

Energy savings: about a 3-month payback. About 26 metric tons of CO2e avoided per year.

Facilities stayed in control

Overrides at the zone or building level, visible on the BMS front end. Hot/cold call processes didn't change.

Want results like these in your buildings?

Share your BMS and lighting controls, and we will assess whether your building is a fit.

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