The Information Model That Powers Fault Detection and Diagnostics (FDD) Whitepaper
February 18, 2022
New whitepaper highlights how Information Models – the “brain” that analyzes building data – differ, and what is required to go beyond fault detection to fault detection and diagnostics.
One of the core components of Fault Detection and Diagnostic (FDD) software is its Information Model.
The Information Model analyzes the building data and produces the diagnostics that help building owners derive energy savings, operational savings, and better performing equipment.
Not all Information Models are created equal. Some are driven by static rules and others by deeper, more nuanced logic.
Rule-based Information Models can be less effective because data from buildings is imperfect. This can lead to a lot of time fixing messy building data.
Clockworks software accommodates the complexity of imperfect building data. The team of people at Clockworks Analytics have spent more than a decade improving the Artificial Intelligence (AI) that helps to run Clockworks. Each new building that the AI sees, enhances the expertise of the system. The company helps the AI learn, the AI helps the software improve.
The Information Model That Powers Fault Detection and Diagnostics (FDD) whitepaper explains how our expert system works together with our information model. As a result, we offer an FDD solution that relies less on actual human experts to identify root causes and produces fewer analysis errors. That’s the difference in the Clockworks approach. It’s the difference between a single, and siloed fault, and a table of issues with diagnostics prioritized across your whole building or portfolio.
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