In late 2013, the research firm Gartner estimated
that the “Internet of Things” – the vast network of
automated pieces of hardware that are individually connected to the Internet – would consist of 26
billion devices by the year 2020, a number that does
not even include laptops, tablets and smartphones
(another 7. 3 billion). Hundreds of millions of these
devices will be located in buildings.
Facilities are only beginning to harness the possibilities of such incredible interconnectedness.
Arrays of sensors on building systems like HVAC and
lighting are now part of the Internet of Things. They
are not just monitoring status and alerting facilities
to malfunctions; they are constantly capturing data
and sending it to the cloud. But managing the sheer
volume of this data presents its own challenge.
“As you add more sensors, you add more power,”
Measure More to Manage Better
says David Kollmorgen, an international director
with JLL who leads the firm’s business intelligence
practice. “But you also add a lot more data. Each
layer makes the data set grow exponentially, not
The usefulness of this data extends beyond vari-
ance analyses and if/then scenarios, Kollmorgen
adds: “What we’re starting to see is data scientists
looking at these huge clusters to identify patterns
that we haven’t even thought about yet.”
This is the true value of “big data” – a collection of
information so vast as to be indecipherable with-
out the aid of advanced computer-driven analytics.
Facilities are just approaching the frontier of these
capabilities. But a cottage industry has already devel-
oped to help companies capitalize now. Learn how
you can take advantage.
“We are taking big data in the direction of managing operations and utilities,” says Logan Soya,
founder and CEO of Aquicore. Soya’s company uses
web-enabled sensors to rapidly collect consumption
and equipment operation data.
“Buildings are going from a dozen data points on
a utility bill to real-time data reported every 30 seconds,” he says. For a simple building, that extrapolates to over 12 million data points in a year. For a
more complex building with multiple submeters or
a large portfolio, the figure quickly escalates into
“The sensors are BAS-agnostic,” explains Soya,
“and it’s a cloud-based platform, which means a
manager at any building can have decision-making
data within a few hours of installation.”
For one client, that data revealed that the en-
ergy consumption curve of one building showed an
unexpectedly high base load. Further analysis then
flagged the heat pumps as the source of the abnor-
mality. Upon examination, it was discovered that the
relays between the pumps to the BAS were not con-
nected properly, which meant they had been running
continuously at night despite the indication from the
BAS that they were shutting down as scheduled.
“The solution was simple and cost practically
nothing,” notes Soya, “but it would have taken for-
ever to find without the analytics.” As a result, the
building will save $80,000 in annual expense, far
exceeding the upfront cost of the sensors.
This data has tremendous value even when there
is no obvious malfunction to correct, Soya adds.
“We have seen buildings raise their ENERGY
STAR ratings by 50 points and save hundreds of
thousands of dollars as our tools help them optimize
scheduling,” Soya says, noting that the value extends
even further when the data feed indicates increased
stress on equipment, often indicating an impending
“It’s like giving a car a full dashboard when it has
never even had a speedometer before,” Soya says. “A
lot of buildings are still working with static monthly
bills, so there is a lot of opportunity out there.”
The machines are coming – indeed, they are already here – and they are talk- ing to each
other. But rather than
being the villains in a
science fiction movie,
these machines are here
to help. They connect our
homes, cars and workplaces
to the Internet in the quest
to make life better.