Digital Twin Fabrication of Harper's Office Space
As my summer intern project at Harper GC, I spearheaded a digital twin of Harper GC's office space. This digital twin had the goal of improving asset tracking and workspace efficiency within the BIM office.
Ideation of Digital Twin
A digital twin is an exact replica of a real-world space that allows individuals to interact virtually with this physical environment. They are often integrated with real-time operational data and asset tags. In the realm of civil engineering and construction, digital twins can be used to track weather data, delivery data, equipment tracking, and IT set-ups. They can also assist BIM management in predicting future issues and lowering costs.
We decided to construct our digital twin using a laser scan of Harper's HQ office as the base for our model. This office setting is a much smaller scale than what one may see on an industrial or construction level, but still reinforces the usefulness and relevancy of digital twins.
Data Integration
Our digital twin was configured using the Amazon Web Services (AWS) Cloud. Within this model, we wanted to keep track of five distinct data flows. The first is desk occupancy, which would keep track of whether or not an office spot is being used. Within the BIM office, members are constantly moving in and out of the office, so it is difficult to know whether or not there is an open desk spot. The next data flows are office temperature and office humidity; with so many computers, monitors, and hardware in use in such a small setting, we wanted to see how temperature and humidity fluctuate throughout the day in the BIM office. The last two data flows are computer temperature and CPU utilization; we wanted to take this data and create a predictor of computer performance and computer speed. We also created a system of asset tagging within the office to keep track of the most important assets in the office.
To better interface with our digital twin, we decided to construct our own sensor to track all of this data, rather than using an already constructed sensor. Our sensor consisted of two DHT11 sensors, a breakbeam sensor, and an Arduino Nano 33 IoT board, all of which are run through an Arduino IDE script. The design model and actual circuit is displayed below.
From there, data was sent to the serial monitor and read in Python. Our Python script compresses, packages, and sends this data to AWS IoT Core through an MQTT communication protocol every 15 seconds. A series of AWS rules and policies organize all of this data in Amazon Timestream, where data is then associated with certain components of our digital twin in AWS IoT TwinMaker. Finally, we constructed an Amazon-managed Grafana dashboard that would display the entirety of our digital twin in a user-friendly format. Below is an outline of the complete data flow in our digital twin, and the code for this project can be found here.
Final Product
At each desk space within the BIM office (and most other office spaces at Harper), there is a laptop stand that is always occupied when someone is using that desk. We decided to redesign this laptop stand and integrate this model with the system of sensors outlined in the previous section. The original laptop stand and our new laptop stand is displayed below.
Grafana Dashboard
The Grafana dashboard is our end product and is what we intend for Harper employees to use on an everyday basis. This dashboard displays our digital twin with all data flows and asset tags. By clicking on an asset tag on the left (marked with a yellow circle), you can view the specifications for this asset and a link to buy a new one of these assets.
The graphs on the right show the office temperature and humidity as a time-series, as well as the most recent reading for temperature and humidity. The text box in the bottom left of the dashboard specifies whether or not that desk is open. In addition, the computer temperature and CPU utilization is graphed together to create a predictor of computer performance and computer speed.
