There is a lot of buzz in the commercial buildings industry right now about how Big Data is going to greatly influence the way buildings are operated. Although the amount of data collected in buildings, even with all of the sensing available, is relatively small when you look at everything that falls under the Big Data umbrella, we’re not exactly talking about “little data” here.
We all know that commercial and industrial buildings eat up a substantial amount of the United States’ overall energy consumption (18.9 percent of total U.S. energy consumption in 2009, according to the Department of Energy). It’s also fair to say that the mechanical and lighting control systems operating in these buildings generally operate less efficiently than modern systems make possible (the DOE also notes that space heating, lighting and space cooling represent nearly half of commercial site consumption).
If we take these two assertions as fact, or at least reasonable probabilities, then it’s time to get familiar with the business intelligence tools that are available to help reduce the amount of energy we require to operate buildings. A good place to start is by identifying when systems in a building are not operating efficiently.
DataEye Pro™ Defined
Mechanical systems within buildings keep the buildings comfortable for occupancy. These systems contribute to the health and safety of the people occupying the buildings and are critical in most commercial buildings because they maintain temperature, humidity, and carbon dioxide levels. With the growing trend of large common work areas and flexible work spaces within commercial buildings, the demand on these systems varies greatly throughout any given day, week, month and season. What is less common is for the mechanical systems to smartly respond to this variation in demand, instead creating a lot of wasted energy consumption. Every day, engineers all over the world are creating innovative sequences to solve this problem.
DataEye Pro™, a tool created by Controlco under its CSI software extension that works within Niagara AX™ Framework by Tridium, (this is an important distinction that is expanded-upon below) to give building managers access to their energy systems’ current and historic data.
As the current implementation approach changes building to building, requiring custom strategies developed by different contractors for each control, managers achieve inconsistent results from one property to the next. DataEye Pro™ solves this problem by eliminating the need to distribute the same sequence across multiple control systems, allowing one data model (also referred to as “semantic tagging” by Tridium and others across the industry) to run against the entire data set.
The DataEye Pro™ strategy can exist in the cloud, whether it is hosted by a data center in New York or on a virtual server in the corporate data center. Though the strategies are no different in DataEye Pro™ than they are in the other control systems, the distinction is that the strategy is executed against a data model, allowing it to be scaled across several buildings simultaneously, delivering consistent results every time.
The potential problem with this concept is that similar mechanical systems are inherently different in the way they operate. This requires the strategy to have variables that are optional, which execute different parts of the strategy when certain variables are absent. The beauty of DataEye Pro™ is the data model.
When modifications are made to the strategy, they are made across the portfolio. If the modification is significant, the strategy is simply replicated and configured to execute with different data tags in the model. The benefit to DataEye Pro™ as an extension of the Niagara AX™ Framework is that the strategies are created in an environment familiar to thousands of Niagara AX™ certified technicians around the world. Adding the power of the DataEye™ data model to the strength of the Niagara AX™ data normalization tools makes for a solution equaled by no other.
Now, to understand how DataEye Pro™ can assist in detecting when mechanical or lighting control systems are not functioning well, we must look at the information required to detect the poorly functioning systems.
In order to know if a system is working properly, one must understand how it normally works under the current conditions. This means the data engine must have some historical perspective to compare against the real-time values. As an extension of the Niagara AX™ Framework, DataEye Pro™ accesses the Niagara AX™ history database for each of the data points in the model. The DataEye Pro™ analytic formula executes against the data model, accessing real-time and historical information to make smart decisions.
Once the information is gathered, DataEye Pro™ can trigger an alarm, using the Niagara AX™ alarm engine, trigger an additional formula, annunciate on a graphic, email a building engineer, send an SMS text message, or execute other logic built in Niagara AX™. These DataEye Pro™ alarms are also known in the industry as faults or Sparks™. The bottom line: DataEye Pro™ allows analytic formulas to result in near real-time and historical fault detection.
The power of being a true software extension of the Niagara AX Framework™ is again realized here since these formulas can execute against any data integrated into the framework. Formulas can be built using the commonly understood wiresheet programming environment for this data. Extending this idea further, it is possible to build other analytic and fault-detection formulas for power data, financial data, gas energy, water, or any data that can be normalized by Niagara AX™. The possibilities are tremendous.
For more information regarding the Niagara Framework™ or DataEye Pro™, contact Controlco.