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agement efficiency, and sustainability. In many cases, Machine learning: This is AI that enables the most
customers are amplifying the insight of smart building sophisticated demand management via intelligent
analytics with advisory services supported by data scien- building analytics platforms. In the context of creating
tists and engineers. These engagements are designed to a building as an energy asset, machine learning is auto-
drive ongoing system performance and even direct OPEX mated process improvement directed by the algorithms
and CAPEX investment strategies for longer-term busi- inside intelligent building devices. For example, machine
ness benefits. learning enables the continuous change in settings and
operations of major energy loads such as HVAC without
AI Embedded in the Smart Building as an the intervention of human analysis. The orchestration of
Energy Resource control and automation across all energy loads within
the facility is an important step in creating the intelligent
Once again, consumer technology trends can signal building energy asset. Machine learning provides a path-
opportunity in the commercial market. AI has garnered way for computer-directed operational improvements that
the attention of the mainstream media in 2018 with the enable dynamic and real-time demand management as We make connected buildings work.*
news of record-level sales of dueling darlings, Alexa and envisioned for buildings as nodes in the Energy Cloud.
Google Home. There is a lot to be said about their effec-
tiveness, but the relevance in the AI debate is clear—the Self-healing buildings: An optimized intelligent building * Make your workspace work for you. Eaton’s connected lighting systems take the guesswork
public is accepting virtual assistants at scale. Our will- would automatically tune systems and operations to reflect out of managing your facility, seamlessly adapting to patterns and preferences. With solutions
ingness to welcome these devices into the home and the weather conditions, energy signals, and tenant needs. that let you easily manage comfort, productivity and energy savings, it pays to be connected.
scale of interaction are providing an important feedback The building itself would understand current and forecast
loop for the tech industry that will help further refine weather and any potential energy supply changes, along-
AI capabilities. For commercial building owners, the side the preferences of the individual occupants. The oper-
familiarity simply correlates to deeper expectations for ations would continually change to maximize comfort and The Eaton Difference
technology-enabled experiences. Machine learning and reduce costs. Some have characterized this kind of intelli-
self-healing buildings are two near-term examples of how gent building as a self-healing building that could forecast
AI can transform the commercial building experience. future conditions and even plan accordingly. Operations
would reflect forecast energy price spikes, equipment We use a simple,
maintenance requirements, and useful life planning. There systematic approach to
are intelligent building solutions available today that run unlock the full potential
a variety of algorithms to provide this kind of ongoing of connected lighting.
system improvement. There are also a growing number We use connected
of vendors offering applications that optimize HVAC oper- lighting to make what
ations to deliver comfort and reduce cost along the lines Eaton Power Lighting Connectivity Software matters work.
of a self-healing building. AI is positioned to take these Unparalleled Advanced Communications and Software applications
approaches to the next level by directing holistic optimi- knowledge of electrical LED fixtures sensing technology
power
zation across end uses (in building and external systems) and management
in real time, delivering broader impacts such as indoor air
quality for health, wellness, and productivity.

It is unlikely that robots will replace building engineers
and facility managers, but AI can help automate routine
processes and fuel analytics. There is a future for AI in 50 % 20 % 30 % 70 %
the intelligent buildings market to reduce the burden on
facilities staff and executive decision makers when trans- Utilization Time Reduced Savings
lating system diagnostics, prioritized by business needs, rate saved costs
into action. The next wave of early adopters can see AI
as a new kind of intelligent building advisor in their digital
transformation strategy.
Increase utilization rate Gain up to 20% in Reduce 30% in HVAC Save up to 70%
Casey Talon is a principal research analyst with of leased spaces by lost productivity by operating costs through in energy savings
demand driven heating
saving time looking
more than 50% using
Navigant Research. Prior to joining Navigant, real time data on how a for equipment and cooling
Casey worked with both public and private sector space is used
clients as an analyst and consultant at Nexant,
IDC Energy Insights, and Camco Clean Energy www.eaton.com/connectedlighting
focused on energy efficiency, building technologies, sustainability, Follow us on social media to get the
and climate change. latest product and support information.

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