Developing a dynamic digital twin at a building level: Using Cambridge campus as case study

A Digital Twin (DT) refers to a digital replica of physical assets, processes and systems. DTs integrate artificial intelligence, machine learning and data analytics to create dynamic digital models that are able to learn and update the status of the physical counterpart from multiple sources. A DT, if equipped with appropriate algorithms will represent and predict future condition and performance of their physical counterparts. Current developments related to DTs are still at an early stage with respect to buildings and other infrastructure assets. Most of these developments focus on the architectural and engineering/construction point of view. Less attention has been paid to the operation & maintenance (O&M) phase, where the value potential is immense. A systematic and clear architecture verified with practical use cases for constructing a DT is the foremost step for effective operation and maintenance of assets. This paper presents a system architecture for developing dynamic DTs in building levels for integrating heterogeneous data sources, support intelligent data query, and provide smarter decision-making processes. This will further bridge the gaps between human relationships with buildings/regions via a more intelligent, visual and sustainable channels. This architecture is brought to life through the development of a dynamic DT demonstrator of the West Cambridge site of the University of Cambridge. Specifically, this demonstrator integrates an as-is multi-layered IFC Building Information Model (BIM), building management system data, space management data, real-time Internet of Things (IoT)-based sensor data, asset registry data, and an asset tagging platform. The demonstrator also includes two applications: (1) improving asset maintenance and asset tracking using Augmented Reality (AR); and (2) equipment failure prediction. The long-term goals of this demonstrator are also discussed in this paper

RF time of flight ranging for wireless sensor network localization

Abstract – A simple system for measuring the peer to peer radio frequency time of flight between two identical sensor motes for distance measurement is presented. This scheme uses a 2.4 GHz radio, simple real time processing, and offline range extraction. Methods for reducing error from clock offset and multipath propagation are presented and implemented on prototype hardware. Measurement results are presented including measurements taken in a coal mine. Typical ranging accuracies are between 1 mRMS and 3 mRMS.

Communicating power supplies: Bringing the internet to the ubiquitous energy gateways of electronic devices

Saving energy in buildings is often hampered by the lack of detailed information about what is using the energy, how much it is using, and how to automatically and remotely control devices. The problem is especially acute for the large number of small, energy-using devices that are present in both residential and commercial buildings. Most of these products use a switching ac to dc power supply to operate electronic and other internal components. We describe a 'communicating power supply' (CPS) to enable the communication of energy and control information between the device and a building management system or other central entities. We developed a proof-of-concept system of Internet-connected CPSs and demonstrated both energy reporting and control utilizing a custom, cloud-based information clearing house. If CPS technology became widespread in devices, a combination of automated and human interactive solutions would enable high levels of energy savings