Digital twins are now beginning to be recognized for their ability to monitor a building’s performance in real time. Companies' building projects should include a model that is prepared for this new, data-driven approach to sustainability.
A common vision for the post-pandemic future is the connection of the real world
and digital world. Within the built environment, this concept is embodied by the
“digital twin” — a 3D, virtual replica of an operational building that stores and
displays both static and dynamic data. In this way, digital twins fulfill a
myriad array of new value propositions for a building’s owner.
The digital twin originates from building information modeling (BIM),
which is the common technology in today’s design and construction industry. BIM
not only unlocked digital 3D design as the new paradigm, it also enabled rich
data and analytics tools to be applied against the design. Chief among these are
building sustainability and performance, building operations and maintenance,
and occupant health and wellness. Simply put, digital twins are the activation
of these metrics and analytics through BIM in the building operations phase.
Static and dynamic data types are at the heart of a digital twin. Static
data reflects building assets that are fixed in place. Commonly, this data
includes room names, room areas, fixed equipment, furnishings, finishes, etc.
Metadata can also be incorporated into any item to record asset provenance,
warranty information, operation manuals, maintenance schedules, etc.
Dynamic data, on the other hand, supplements static data and records
information from building components that are ever-changing and increasingly
driven by embedded building sensor technologies. Also known as the “Internet of
Things” or IoT, sensors are a
fast-emerging market and are just beginning to demonstrate their potential
impact on buildings. At the simplest level, sensors record things such as room
temperatures, HVAC fan speeds, door entry access, water leaks, indoor and
outdoor air quality, etc. When IoT sensors are coupled with simple algorithms or
even artificial intelligence, they gain the potential to do extraordinary
things. Examples include counting room occupants and monitoring their engagement
with the speaker, inspecting the health of people queuing on an airport jetway,
monitoring environmental health and airborne or waste-stream-borne pathogens,
predicting maintenance needs, and much more.
Value propositions for a digital twin
Performance analytics platform
-
At its most basic level, a digital twin serves as a live dashboard providing
real-time data on the utilization of building assets. Through a user
interface, building operators can query any object represented in the
digital model. If the object has sensors, the live data is displayed in real
time (historical data can be examined, as well).
-
Deeper uses include applying data analytics for predictive purposes — such
as maintenance needs, maintenance schedules, pre-ordering of parts, and
elimination of waste in labor and materials. These predictive capabilities
decrease interruption, expense and risk to building operations.
Data warehouse for a material passport
- A material passport is the equivalent of a food nutrient certificate for
building materials. It documents all the materials used in a product or its
construction. Since a digital twin is — by all intents and purposes — a
database, this is the perfect platform to collect provenance data from the
original material supply chain and associate the records with their virtual
equivalent. This enables building operators to plan for maintenance and
obsolescence; or to transfer material data to an exchange; or a new material
passport, when the asset is removed from the property. If we reimagine
buildings as material
banks,
this type of data warehouse would serve the emerging market of material
exchanges that trade the value of recovered materials for reuse after
upcycling or recycling.
Planning tool
- As a virtual simulacrum of a built property, a digital twin can be used by
architects to explore remodeling scenarios and their potential performance
under different lenses — such as energy use
intensity,
material reuse, construction cost and re-fit schedule. In advanced
applications, new sensors can be tested virtually before being deployed in
real-world conditions.
Occupant metrics and feedback
- By utilizing advanced sensors and incorporating third-party software
applications that measure or solicit occupant feedback, a building owner may
gain valuable information regarding how a building is experienced. This
collated data may lead to changes in environmental conditions,
reconfiguration of amenities or wholesale remodeling of spaces, or mediating
distasteful elements such as smells or finishes. Other environmental factors
such as air quality or temperature; or lighting can be monitored virtually
and adjusted for optimum human performance, health and wellness in real
time.
Proof of performance database
- Ultimately, a digital twin is a database to be used by the real estate
industry, where buildings are increasingly valued according to their real
and potential
performance. Through the data embodied by a digital twin, a building owner can provide
proof-of-performance when a building goes to market. Additionally, cities
and other jurisdictions are starting to require periodic recommissioning of
buildings to certify that performance remains within the original design
specifications or within a codified standard. With a digital twin, embedded
sensor data could potentially measure building performance in real time and
provide certification-level data on a continual basis, thereby bypassing the
need to engage in the intrusive process of commissioning.
Digital twins are just now beginning to be recognized for their potential to
inform users of a building’s performance in real time. For those companies with
building projects on the horizon, now is the time to expand your deliverables to
include a building model that is prepared for this new, data-driven approach to
sustainability.
Published Feb 1, 2021 7am EST / 4am PST / 12pm GMT / 1pm CET
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