Modular deployment of microprocessor-controlled data acquisition and control within a digital twin

One major component of building management is the understanding of the current state of the system, typically using sensor measurements. To achieve this, many building managers are interested in the deployment of a digital twin for each building that allows for remote inquiries. However, many commercial data acquisition systems use proprietary connections or data formats putting a large barrier for interoperability between sensors and digital twins. To remove this barrier, this work develops a transparent data acquisition system using microprocessors and the remote connection to this system through a python-based remote digital twin operational platform. The use of microprocessors allows for nearly complete control of the data processing from the analogue to digital converter, data sampling, and data recording. There are many possibilities to process this data, so this paper focuses on identifying the various possibilities and demystifying this computer science topics for engineers. To access this data, a remote connection allows for multiple users to simultaneously access the current operational data. Using an interface, such as the digital twin operational platform, reduces the required knowledge to promote a multi-disciplinary culture through shared data within the digital twin.