HVAC monitoring is a term used to describe the process of continuously tracking the energy consumption and performance of heating, ventilation and air conditioning units within a building, generally with the purpose of alerting operators of faults and inefficiencies.
HVAC is a major contributor to the maintenance and energy-related operating expenses of a property. Without HVAC monitoring, issues with systems may go undetected for weeks. In addition to operating expenses, HVAC problems are a leading cause of tenant complaints.
By installing a building monitoring system that covers the HVAC systems, including chillers, exhaust fans, motors, etc. issues can be detected and corrected in real time. In addition, consumption profiles can be analyzed by machine learning algorithms to predict when issues are going to occur so operators can make minor adjustments instead of major repairs.
The falling cost of sensors for collecting building data and cloud computing for storage and analysis has lowered the barrier to entrance for technology service providers. Accordingly, there has been a proliferation of companies that collect, visualize and/or analyze building operations data.
At the most basic level, these data have been translated into online dashboards that operators can use to get a high-level understanding of what is happening with their HVAC equipment. A few players have developed sophisticated analytics to automatically catch anomalous behavior in the data.
For example, with some historic equipment performance data, analytics can determine an expected power demand from HVAC equipment. If, at any point, the real-time demand does not match the expected result, the software can trigger an alert to notify the building operator.
However, the reality is that “anomalous” behavior is interesting, but it’s not a game changer for building operators. Without more details around the “how” and “why,” this notification still requires an investigation. At best, it results in a faster resolution of an issue and a marginal improvement in maintenance or energy efficiency. At worst, it is a false positive that wasted the operator’s time and created resistance to the technology.
And yet, this type of solution remains prevalent today. The thought of applying machine learning algorithms to automatically identify anomalies sounds like it would provide value by itself, but that is not necessarily true.
The best HVAC monitoring solutions deliver notifications that pinpoint the root cause of the issue.
The anomaly detected by the first provider may prove valuable, but it’s important to distinguish between value on an ad hoc basis, and strategic alignment that continuously delivers value.
Enertiv's Asset Intelligence solution is a highly sophisticated HVAC monitoring solution. Schedule a demo today to see how.