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HVAC asset health & energy use insights

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What our clients say

“Now my team is all across the FitMachines dashboard and emails. Personally, I check the FitMachine Daily Snapshot emails every morning to make sure everything is right, and also check the number of restarts as avoiding these are critical to extend the lifetime of the chillers.”

Glenn Vickery
Maintenance Manager, Contracts
The University of Queensland

Predictive maintenance is the future for commercial HVAC assets

FitMachine generates the insights that allow you to understand HVAC asset health, operating behaviour and importantly energy use – insights that allow smarter decisions to be made.

Smart Buildings programs need smart data from HVAC assets

Keeping chillers, cooling towers, air handling units (and more) healthy

Predict the future

FitMachine’s advanced machine learning technology allows you to adopt industry leading predictive maintenance processes.

Elevate your maintenance

Decrease downtime. Reduce time and money spent on asset breakdowns thanks to advanced predictions.

Visibility of your entire fleet

Know exactly how all assets in your operation are performing in real-time. Accessible anytime, anywhere.

Highly cost competitive

Reduce physical inspection costs, lower operating costs, extend asset lifecycle. And all with a as-a-service commercial model.

Companies around the world trust FitMachine with Buildings & Facilities




Read a Case Study


HVAC – Screw type chiller over-condensing as nights get cooler


The Queensland Brain Institute (QBI) is a world-class neuroscience research facility aiming to uncover how the brain works in health and disease. QBI and the University of Queensland have deployed MOVUS FitMachines® on multiple types of HVAC equipment within those facilities. Request a demo Enquire about a pilot »

What happened?

A screw type chiller was retrofitted with a variable-frequency drive (VFD). After this was installed, the FitMachine® detected abnormal behaviour during the first cold nights of the winter season. This abnormal behaviour was occurring in the early hours of the morning, and the FitMachine® Artificial Intelligence (AI) was able to detect the problem outside of the standard hours for technicians. It issued alarms to QBI due to significant changes related to vibration, noise and temperature signatures.

Client outcome

The chiller is over-condensing and as the nights get cooler we are seeing worse conditions. Over-condensing on a screw chiller is not very healthy at all.

The technology presented to us by MOVUS is 100% useful and I think it has a great future in a wide range of industries
QBI investigation
  •  Adjust VFD parameters to reduce the overall chiller unloading
  • Extend the life expectancy of the chiller
  • Less time exploring the problem as the FitMachine® provided access to real-time data.

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We’re committed to helping commercial property owners and operators better use and maintain HVAC assets

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