The massive adoption of the internet of things ( IoT), data-driven analytics and machine learning in smart building applications has paved the pathway for a transformative technology once used in the manufacturing sector called a digital twin. While the digital twins concept is not new, it is poised to revolutionize the way in which building owners and operators construct, maintain and analyze the uses of assets and occupants in their buildings.
What is a digital twin?
A digital twin is a digital replica of physical assets, processes, people, places, systems and devices that can be used for various purposes. The digital representation provides both the elements and the dynamics of how the Internet of things devices operate and live throughout its life cycle.
Digital twin virtual representation of the physical building is embedded with rich information about spaces and assets and can offer significant benefits to building owners.
The immediate access to data and schematics about how a building is performing can enable owners and operators to manage assets, energy, space and comfort in a free-flowing manner inside of a single building or an entire portfolio of properties.
Some of the best use cases for digital twins have emerged in the often disjointed design and construction process where a loss critical information creates many gaps.
During the design and construction of a building, a considerable amount of information is produced such as drawings, documents and notes, however maintaining and finding this information after construction is often very costly and time-consuming.
Imagine the amount of time it takes a building operator to sift through the documentation to identify how particular areas were constructed to identify an underlying problem inside the building’s infrastructure. While, in the meantime, the building or its occupants continue to suffer as the problem or failure persists.
The digital twin serves as much more than just a database or schematic and is a dynamic, expressive real-time system of record.
While an operator may know that a part needs to be replaced and space needs to be reconfigured, often times it impossible to find the data necessary to make cost-prohibitive decisions- with a digital twin, the process can be easy and reduced from weeks and months to hours.
Whether it’s data generated by an asset, space, lease, maintenance management systems or data from IoT, a digital twin can act as the hub to integrate information provide context to it and generate insights that help to optimize building performance by eliminating silos.
As more builders create digital twins”of properties, it eases labor costs related to the facility management. If an air condition system needs repair- using a digital twin the technician can not only find the fault location on smartphone or tablet but can also better troubleshoot the problem using data captured in the twin. In cases where on-site visits are costly a digital twin provides remote access and more transparency than an actual site visit. Owners can send a digital twin to vendors who can then create models based on its data and reduce the needs for costly visits.
When making capital improvements or deploying a single application across a portfolio of properties, digital twins enable the ability to forecast through modeling the impact in one or many buildings and drive data decisions that can significantly improve return on investment.
For example, now a simple deployment of conference room sensors or an entirely optimized environment in one property can then be replicated and modeled in other locations within a portfolio for owners to more easily quantify deployment and logistical costs.
In retail, hospitality and industry settings where replicating the same customer experience across all locations is crucial to a brand, digital twins provide a living schematic of how and where to deploy IoT devices and sensors. Imagine the number of IoT devices, cameras and sensors that are used a single Las Vegas property or a large retail store- having a digital twin can save significant technical labor costs by replicating the same environment while maintaining the customer’s experience across all properties.