Why the Built World Needs Standard APIs

Lately, new ESG initiatives have come front-and-center as companies seek to contextualize and limit their business’s impact on the environment. This is especially true for the built world—a term that refers to the human-made environment that provides the setting for human activity, including homes, buildings, zoning, streets, sidewalks, open spaces, transportation options and more—where monitoring energy efficiencies is becoming more commonplace and even required by law. For example, a New York City law now requires buildings of a certain size to post an energy-efficiency score at their entrances. Yet, calculating such a score isn’t that straightforward—there’s a lot of legacy technology in use within most large commercial and residential buildings, and pulling data from these systems is notoriously difficult.

A building manager may seek greater visibility into these systems to not only determine a building’s energy score, but to program optimizations, inform building security or enact new digitization. But the answer isn’t to hastily rip out and upgrade old hardware—old equipment like AC units and elevators were built to last 50 years or more and could be functioning seamlessly. Instead, this is another area where REST APIs are set to accelerate by uniting legacy integration software and disparate hardware with a standard layer.

I recently met with Shaun Cooley, CEO and founder of Mapped. According to Cooley, API-driven standards for built environments could open up transparency into hardware component behaviors and the interrelationships between systems within a building. Below, we’ll briefly consider the history of building protocols and look to standards like Brick Schema that aim to unite legacy and modern physical infrastructure. We’ll consider the competitive advantage APIs bring to the built world and how increasing data accessibility could assist operations.

The State of Physical Building Digital Protocols

The built world consists of various digital communications standards. Most buildings have many older on-premises protocols for lighting, HVAC, elevators and other systems. For example, many elevators and fire safety systems were installed by systems integrators in the 1970s and adopted connections using Modbus, a communication protocol based on serial connections. BACnet is also commonly used to control HVAC systems and is a step forward from Modbus in that it can more easily connect to IP networks.

Fast-forward a few decades to the dawn of the cloud; many companies overlaid sensors onto these old systems, explained Cooley. These power-over-ethernet (PoE) or battery-powered systems relay data immediately to the cloud and often speak in proprietary protocols. A single commercial building could easily be juggling a bundle of these various communication protocols, all originating from installations that occurred at different time periods. These nuances mean that you are “constantly dealing with chaos across your portfolio,” Cooley said. There’s so much data, but getting it normalized and usable is very challenging, he said. One must integrate with many sensors and protocols, which he describes as “the dirty plumbing” that no one wants to build.

There’s bound to be differentiation from building to building, too, which could place a further strain on managing multiple building operations. Without a window into building data, it isn’t easy to know things like the current occupancy of the lobby or how occupancy affects energy consumption. Unless managers can connect the dots between systems, it’s impossible to understand the relationships between components.

Making a Data Graph for a Building

For example, take an AC system in a commercial building. Such a unit isn’t as simple as a single-family home’s typical thermostat and furnace. It’s often a mix of a rooftop chilling unit, pipes, pumps and a VAV damper that controls the air. While protocols are good at describing how individual components are performing, the composition of components is really what defines a building’s system and its efficiency, said Cooley.

According to Cooley, instead of adopting a vertical data schema, buildings require a graph data model to adequately represent hardware interconnections. This is why he’s rallying behind Brick Schema, an open source uniform metadata schema for buildings. Instead of a vertical data schema, Brick Schema is built on a graph data model, which enables more descriptive relationships in a system.

End Benefits

Pulling unstructured data from 20 different data lakes into a clean API could allow easier access to new solutions. “We want to make it very simple to build applications for these sorts of environments,” said Cooley. Typically, system integrators must reverse engineer and connect to legacy building hardware, which can become very expensive very quickly, he said. He recommended using a sandbox based on open standards that can easily be rolled out to any building to reduce those hurdles. A more consumable layer with common endpoints could increase developer usability when creating innovative building applications.

Similar to how Twilio made SMS easy, Cooley said he hopes for a similar proliferation in the built world. Many applications could be built with such an abstraction layer. For example, managers could better understand energy usage to reduce consumption, meet regulations and save money. Or, such an abstraction layer could inform predictive maintenance to create automated alerts before failures occur. There are also plenty of ways to improve occupant experience or intelligently optimize the lighting and temperature in a space.

“Entirely new business models and concepts emerge that we hadn’t previously considered,” said Cooley. For example, he described a “tailgating app” that uses Brick Schema for a security use case. The app prevents building occupants from letting other people “tailgate” into the building behind them after someone swipes their badge. To do so, the app interfaces with many separate building systems (the elevator system, surveillance system, telepresence systems and other sensors) to ensure the number of people in the building matches the number of occupants that swiped in. A lingua franca helps to connect the disparate hardware involved.

The Future of Building Automation

This is by no means the first attempt to standardize building data. For example, the Green Button Initiative provides a standard API through which to download a utility use data for electricity, gas and water and share it with solution providers. However, according to Cooley, this information only goes so far. Building owners will require more contextual data on-site.

For example, perhaps a building’s window glazing is causing specific rooms to overheat in the sunlight. Thermal sensors would spot this condition, but bulk energy consumption readings wouldn’t ascertain the root cause. Access to real-time granular data such as current occupancy count is also necessary for developing on-site applications that better refine exactly how human involvement impacts energy consumption.

Of course, as building systems become more intelligent, there is the growing possibility of privacy infringement. For example, systems that use facial monitoring and recognition could end up storing personally identifiable information. In that case, you “need to give data owners the control to decide what applications can’t or can’t access PII,” said Cooley.

While this field has many read-only applications, Cooley predicts future write operations will enable more automation with building hardware. This could allow applying ML/AI to anticipate elevator floor calls. Or, a predictive system could cool a room only when a meeting is scheduled. When such data is readily accessible and available for developers, it presents many innovative opportunities to optimize and interact with the built world.

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