Fault detection in 2012 represented 27 percent of the $16 million global market for building analytics, with building optimization accounting for the remainder. However, as the market develops and grows, fault detection will take a larger share of the market, IHS forecasts.
Big data is a term used to describe large and complex data sets that can provide insightful conclusions when analyzed and visualized in a meaningful way. Buildings are full of systems that produce data, from building management, which captures temperatures and humidity levels, to access control, which collects occupancy statistics.
“The challenge for big data in smart buildings is to combine the silos of information from different systems into a single unified location where the data can be analyzed,” said William Rhodes, senior market analyst with the Building Technologies Group at IHS. “Some systems allow for an Internet Protocol (IP) interface, whereas others require acquisition and transformation of the data before it can be combined. Data naming and labeling is critical at this point to ensure consistency across buildings and equipment.”
After the data is combined it needs to be normalized in order to adjust for seasonality, measurement scales, and other factors that may skew the findings.
“Once combined and normalized, the opportunities for big data can emerge,” Rhodes said. “Analytics and algorithms can be run on the data to identify operational and energy savings. Fault detection and building optimization are the two primary methods to drive savings and provide quick payback on the cost of installing the solution.”
The final step is to provide big data analysis to the relevant stakeholders. The facilities team needs a dashboard to show where the faults are, or will be. In contrast, the chief financial officer requires a dashboard to reveal where the savings are being made.
Ultimately, the big data opportunity for smart buildings lies in achieving savings and improving the bottom line.
Publication date: 7/29/2013