HENDERSON HEADLINES DIGITAL TWINS: A KEY TO EFFICIENT BUILDING OPERATIONS Authored by: Adam Roth | October 14, 2021 Our design approach at Henderson Engineers is centered around processes that deliver quality in the most innovative and efficient manner. Digital twins, which are virtual, identical representations of the building systems we design, assist in making informed decisions during every stage of a building’s life cycle. By integrating Building Information Modeling (BIM), the Internet of Things (IoT), and machine learning, digital twins update and change in synchronization with their physical counterparts. Unlike a static data model, a digital twin continuously learns and updates itself from multiple sources to represent its counterpart’s near real-time status, working condition, or position. This connection of design data and as built data to sensor data and controls brings a building’s digital twin to life. We can therefore learn from the twin over time and use building system IoT platforms – from dropin boilerplates to fully custom setups – and machine learning to aid future design as well as predictive analytics for the building. The possibilities enabled by this technology are only limited by our imagination. At Henderson, we’re using digital twins to help shape general IT solutions for buildings with best practices for selection, implementation, and operation. The solutions are different depending on whether you’re interested in simply knowing what happened to an asset versus predicting when it might happen again. Solutions also vary when dealing with a single building versus a campus or a fleet of stores. And as lifelong stewards of the building systems we design, data security and data resiliency are key components to our vendor selection process. Timely management of a building is critical, and remote monitoring and remote control are very different concepts. Based on a client’s needs, digital twins can enable systems to provide simple reporting information to help facilities managers make decisions and even offer recommended
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