Reducing energy costs and keeping occupants comfortable and productive have driven early adoption of building automation systems.
Automation typically saves $0.20 to $0.40 per square foot in utility costs per year. For an average-size building of 75,000 square feet, that means a savings of $15,000 to $30,000 annually. Automation not only saves money, it gives owners better control over the indoor environment, creating a healthier, more pleasant atmosphere for workers and customers.
Systems such as lighting, heating, ventilation, and air conditioning (HVAC) are key to the overall comfort and experience of building occupants; when these systems fail, it can result in a loss of productivity and revenue–a 94% increase in air quality can result in a 40% increase in employee-reported productivity.
But building automation systems have limitations. Automation began as an industrial solution, and legacy systems still in use were designed for full-time, on-site facility engineers. These systems lack the ability to stream and store the vast amount of data required to analyze trends across a portfolio of buildings. As a result, ongoing system problems can go undetected.
But now IoT and cloud technologies are being applied to buildings and the equipment that keeps them running. New solutions enable facility managers to gain deeper insight into how well their equipment functions, if they’re meeting their energy goals, whether they’re keeping occupants comfortable, and much more.
Cloud-based building management provides solutions that deliver three key business benefits: reduced costs, better productivity, and enhanced security—as shown in Figure 1.
Connecting the Unconnected
But even as building systems become smarter, they remain siloed. HVAC, power, lighting, security, and other systems are typically scattered among various, incompatible platforms, protocols, and management tools. It’s time-consuming and costly to gain insights, optimize energy use, and monitor equipment health within one building, let alone across many.
Riptide, a cloud-based building management solution provider, developed the Enterprise Portfolio Management System to address these challenges. Built on Intel® technology, the system integrates data from individual automation systems within a building—or in multiple buildings—and enables managers to see real-time results and manage settings from a centralized location.
“We think of a building automation as a single system, but actually it’s a collection of industry subsystems,” explained Marti Ogram, vice president of sales and marketing for Riptide. “Electric power, HVAC, refrigeration, and lighting are provided by separate vendors, and each has its own industry standards and protocols. We unify all those protocols and bring them together in a single environment.”
That means building managers can set predefined schedules for temperature, lighting, and ventilation on one platform. They have real-time visibility and control over equipment and energy use for all systems and every building.
Riptide collects data via smart sensors across a single building’s or portfolio of buildings’ different control systems regardless of the vendor. Data can be processed via an on-site gateway that gives managers swift control over their lighting and temperature settings. It also ensures that managers stay in control if a connection to the cloud is lost.
A full set of data from all sensors is sent securely to the cloud, where it is analyzed to spot brewing problems, provide notifications to service technicians, and gather insights about equipment and energy trends. (See Figure 2 below.)
Cloud computing and high-performance Intel processors allow Riptide to analyze and relay information quickly. “Old legacy systems suffer from using a client server architecture. We need cloud computing power to do the heavy lifting for data analytics and machine learning,” Ogram said.
An equipment management solution like Riptide’s also allows for easy expansion as new sensors—or new buildings—are added to a portfolio. Because they’re no longer confined to the capacity of an on-premises server, building owners can collect far more information than they did in the past.
In addition to adding capacity and speed, cloud-based analytics enables building owners to find equipment problems early, preventing breakdowns and saving time and money.
For example, when an air conditioning compressor starts to fail, it expends additional energy to keep going. An owner who isn’t aware of the problem receives a higher electric bill without knowing why. Finally, one hot day, the compressor shuts down completely, leaving occupants sweltering while the building manager urgently arranges for repair.
With Riptide’s system, data analysis can uncover the incipient malfunction and send an alert to a service technician via a mobile app. The technician would know that a problem exists, and learn more about it before loading up the truck and heading to the site.
Viewing the analytics, a technician might learn the compressor is 10 years old and received three work orders in as many years. As a result, the technician would bring a new unit to the building instead of wasting time and money tinkering with the old one. The problem would be solved on the first visit, before a breakdown occurred.
Big data also gives building owners new insights about their energy use. They can slice and dice the data however they want, benchmarking equipment performance against industry standards, checking occupants’ compliance with set points, measuring energy use at different times of the day, or comparing one building’s performance to another’s.
Managers at Nordstrom use Riptide’s analytics to manage their controls systems and eliminate unnecessary lighting across 300 stores. The premium retail chain achieved a 25% reduction in its biggest maintenance budget line item—HVAC repair—by using the Riptide solution to verify fixes went right the first time.
By examining big data trends, building owners can estimate their future energy use and anticipate equipment repairs, helping them create more accurate operating budgets. They also gain a better understanding of how occupants and customers use their systems, leading them make to better-informed decisions about controls and future equipment purchases.
The more information sensors collect, the more helpful they can be. Riptide is now starting to work with Intel and other partners to apply machine learning techniques to the vast troves of data it has collected. Over time, the insights it provides will predict equipment failures and self-adjust building systems based on weather and occupancy.