C+S July 2021 Vol. 7 Issue 7 (web)

sets will greatly facilitate the project. Some CAD files can also be too detailed or complex for real-time renderings. Therefore, it is important to use a development platform that can intelligently transform files to lower resolution without losing critical details. Geo-referenced data sets for data overlays come from a wide variety of sources including IoT sensors, municipal data, digital feeds from pub- lic data providers, or location-based workflow apps (such as inspection or approval processes). Some data may also be incomplete, contain errors, or reside in legacy systems with a nonstandard format. Wran- gling the correct data is critical to developing an accurate digital twin platform. A generative system to synthesize missing data and conform outlying data is a key capability for success. IoT data pipelines can be massive. Because of this, it is a best practice to use data transformation tools to aggregate and summarize the data for visualization. When doing this, unifying location across various data sets can be quite complex. To simplify the process, platform sys- tems can unify data using 3D geofencing, point of interests, and GPS snapping systems. Umajin Wynn Hotel IoT demonstration—CES 2020 – real time tracking of assets

Return on Investment of Digital Twins in Project Management The initial effort in identifying and cleaning data sets is not insignifi - cant, but it can be effectively managed with appropriate expectations and tools. If multiple projects are planned for a given area, using multi- experience development platforms becomes a valuable resource for future activity. The cost of creating digital twins has been dropping, and they are expected to become a more commonly used project planning and man- agement tool. The benefits of digital twins, including faster approval cycles, lower and more predictable construction costs, and greater cli- ent satisfaction, can greatly improve project economics. We see Digital Twins moving forwards as a fusion of real time, people-focused data sets and the traditional building and process-based BIM systems.

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