A digital twin is a digital representation of a real-world entity or system. In the context of a building, digital twins express the location and characteristics of every wall, door, and window, but also every pipe, cable, and switch in a virtual model. In our increasingly smart buildings, digital twins must also mirror every system, device, and connection to truly represent the facility. Buildings are not static entities, however, so to maintain an accurate digital twin the system must also monitor wear, tear, and repair, and realize every modification or upgrade, in the digital model. With many traditional assets and an estimated 1.7 billion connected sensors and endpoints in commercial buildings in 2020, the digital twin has its work cut out.

According to the tech research firm Gartner, 75% of organizations implementing Internet of Things (IoT) technologies already use some form of digital twin or plan to within a year. While 54% of respondents in their survey reported using digital twins to serve only one constituency, the year-on-year results show digital twins increasingly serving more than one, with nearly a third of respondents now reporting multiple digital twins serving multiple constituencies. The constituencies of a smart building may include IoT device manufacturers, repair and maintenance, or user-focused operational processes, for example, each requiring a different type of data from the digital twin ecosystem.

Multiple digital twins acting in unison will be complex and inevitably too complex for straightforward integration. Multiple digital twins need the tools to bring all their information together to create a “digital master” and then manage any changes to that digital master for all systems and user processes. Therefore, a platform is required to test, deploy and manage each digital twin based on the digital master, integrating multiple digital masters to implement numerous digital twins in a building. Such a platform should be able to update and provide the exact state for each individual digital twin, creating a single and reliable source of truth.

Organizations should be able to use their digital twin platform to create visualizations, dashboards, and in-depth analysis of live data from multiple digital twins. The live data should be linked to the digital master to allow for accurate and real-time drill-downs into design documents or other components of the digital master. It should be possible to set up events, such as scheduled maintenance based on live data of the current maintenance status of the physical asset. And, the platform needs to provide a user perspective in order to enable collaboration between various building stakeholders.

“A digital twin is a digital representation of an entity, which is sufficient to meet the requirements of a set of use cases. However, the lack of interoperability between the digital twins of different companies hinders use cases that require information exchange between different organizations. Achieving interoperability among digital twins requires transforming the included information to other formats,” reads a December 2020 paper by Platenius-Mohr et al. “A solution that enables engineers to flexibly define transformation rules, and apply them to IoT systems, where the result can be accessed in a file-based and in an API-based way.”

For the functional and efficient development of buildings, digital twin platforms must provide an open Application Programming Interface (API) that allows any system to interact with the master digital twin. APIs are software intermediaries that serve as information gateways to allow two applications to talk to each other and have become a standard fixture in connected platforms. From the internet to smartphones, to all manner of digital services, APIs are a cornerstone of the modern digital experience, and through open platforms like Eclipse Ditto, for example, the API model can facilitate the development of advanced digital twins for buildings.

“Eclipse Ditto is a technology in the IoT implementing a software pattern called digital twins” reads the official documentation of the open platform. “Ditto is not another fully-fledged IoT platform. It does not provide software running on IoT gateways and it does not define or implement an IoT protocol in order to communicate with devices. Its focus lies on back-end scenarios by providing web APIs in order to simplify working with already connected devices and “Things” from customer apps or other back-end software.”

Big tech firms are also getting involved in the unification of digital twins in smart buildings through strategic partnerships and projects along the semantic tagging route. Through a partnership with smart building ontology RealEstateCore, Microsoft has created Azure Digital Twins as an underlying Digital Twins Definition Language (DTDL) at the heart of its Smart Building solutions. The DTDL is a blank canvas that can model any entity, by providing a common domain-specific ontology to bootstrap solution development, as well as seamless integration between DTDL-based solutions from disparate vendors.

Similarly, Salesforce and Siemens have teamed up to deliver a workplace-focused device integration platform. The partnership combines Salesforce’s Work.com products with smart infrastructure services delivered by Siemens, including its Comfy and Enlighted “internet of things” applications. The service is essentially a resource that provides companies access to a “command center” application that serves as a common interface for digital workplace tools such as access control and occupancy management systems.

Meanwhile, Google created its Digital Buildings project, an open-source, Apache-licensed effort to create a uniform schema and toolset for representing structured information about buildings and building-installed equipment. The Digital Buildings project originated from the need to manage a very large, heterogeneous building portfolio in a scalable way, by enabling management applications/analyses that are trivially portable between buildings. Integration is achieved through a combination of semantically-expressive abstract modeling, an easy-to-use configuration language, and robust validation tooling.

Progressive startups like Mapped are also finding ways to enact the API model for digital twins of smart building data. Mapped makes a physical device that plugs into a variety of systems to ingest building data and send it to the cloud for analysis. After ingesting the data, Mapped’s device analyzes it to provide a map of what devices are on the network and which devices each one can talk to, then makes that accessible to developers through an API. So if the data is BACnet, Modbus, IFC, or any other format, Mapped pulls it in and then spits it out in a unified format that developers can work with.

“Over time, digital representations of virtually every aspect of our world will be connected dynamically with their real-world counterparts and with one another and infused with AI-based capabilities to enable advanced simulation, operation, and analysis,” says David Cearley, vice president, and Gartner Fellow. “City planners, digital marketers, healthcare professionals, and industrial planners will all benefit from this long-term shift to the integrated digital twin world.”