Smart Buildings Are Stupid Hard. Here’s How To Fix Them
Every one of us has a magical tool in our pockets or purses. We should be able to enter an unknown building, navigate to our desired location, know where the elevators are, and gain access seamlessly.
But we can’t.
Our buildings cost millions or even billions of dollars. They have the latest technology. But they don’t know how many people are in them. They don’t know when to turn the lights off, or learn when to start warming or cooling office or meeting space. They don’t reposition elevators for maximum efficiency, and they can’t tell first responders where the fire is, where the medical emergency is, or what the quickest route up is. Nor can they tell occupants that the air is clean today, or that there’s an elevated level of volatile organic compounds because the floors were just waxed yesterday.
Why?
Because they are all snowflakes.
“The problem is that most smart buildings are actually bespoke,” Mapped CEO Shaun Cooley told me in a recent episode of the TechFirst podcast. “They are custom built for that one instance, that one physical building that exists somewhere in the world.”
Cooley used to be Cisco’s chief technology officer. The day after he left Cisco in June 2019, he started Mapped because he had watched too many companies buy technology but not be able to benefit from a solution.
They had all the hardware. But the little bits and pieces added up to less than the sum of the whole. Significantly less.
And that meant that every smart building or smart city project had to reinvent the wheel over and over and over again.
“These were sort of Fortune 50 type companies who would build an amazing prototype and amazing proof of concept in a single factory, or a single building, or a single mine, or a single refinery … and then they would go to move it to the next one,” Cooley says. “And they would start from scratch again. And so what was originally sort of a 12-month project ... turns into another nine months over there. And then somebody does the math of ... we’ve got 95 refineries, or we have 4,000 buildings times nine months, and these projects would just get canceled.”
Listen to the interview:
Part of the problem is that for every component in a building — HVAC, lighting, fire safety, elevators, security, surveillance, access controls, irrigation, and more — there are 20 to 100 vendors, Cooley says. And each vendor has dozens of contractors or integrators who actually install the components.
All the vendors are making smarter and smarter components with chips and sensors and motors and data dashboards ... but all of them are separate.
That means a single building is an aggregation of hundreds of incompatible parts that don’t connect, don’t communicate, don’t even recognize the presence of other mechanisms, and therefore can’t function as a cog in a coherent, functional, interdependent system.
That makes each building a one-off unique snowflake.
And it makes them unmanageable.
“The folks who own portfolios of buildings — whether it’s a large sort of company that owns and occupies them on their own, or a company like a CBRE, or Boston Properties that owns and operates a bunch of buildings for others to occupy — none of them look the same, and so the definition of what is a smart building is really, really hard to answer,” Cooley says. “All of those unique snowflake systems are very hard to orchestrate at a portfolio-wide level.”
Mapped isn’t trying to solve all the problems that smart building represent.
What Mapped is trying to do is make heterogeneity understandable, manageable, and uniform by putting a data translation layer between all the parts and the people who want to know: are my buildings functioning well? Are the lights on? Is the heating working? What is my occupancy rate? Is my air healthy to breath?
“The layer that we’ve put in between what’s installed in the physical environment and the applications that either you as an owner/operator/tenant are building or the applications that you’re acquiring from third parties, that layer is really that normalization layer,” Cooley says. “We pull in the data from all those disparate sources, make it look exactly the same.”
Eventually, that will lead to manageability of buildings at a holistic scale, even over portfolios of dozens or thousands of structures.
And ultimately, that will layer up to smart cities.
One example: a building like Salesforce Tower in San Francisco. Assuming full occupancy, it unleashes tens of thousands of workers from a million square feet of office space every night at 5PM, helping turn the South of Market district street grid into a parking lot. Smart systems might alert San Francisco building systems as people leave, enabling smarter routing and intelligence traffic control. City-wide, that could lead to cities incentivizing different start and closing times to spread traffic over more time, easing flow.
Mapped thinks data aggregation software is the key to unlocking intelligence at the building and city level.
“It is very hard to get software into a factory. It’s very hard to get software into a refinery or into a smart building,” Cooley says.
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