Evaluating Digital Twin Technology and Internet-of-things Sensors for Informed Asset Management

Project Information

Link to Latest Report: Coming Soon


As a transformative technology, “digital twins” have the potential to modernize and optimize bridge operation and maintenance, leading to improved asset management and bridge longevity. The value proposition for bridge owners is that in paying the upfront costs to build and maintain a digital twin of a physical asset, they can make better decisions and make better use of limited preservation funds. To realize these benefits, Internet-of-Things (IoT) sensors are used to monitor critical infrastructure components and are integrated with other data streams, as well as more conventional inspection activities to enable a rich, digital representation and historical record of real-world conditions. This proof of technology project will provide near real-time, integrated data on the conditions of a floating bridge in Washington State that can be used to inform operational decisions about bridge closures, send alerts to operations and maintenance personnel when anomalies and issues are identified by the sensors, and a provide historical record of bridge performance correlated to traffic and weather conditions with which to base future asset management decisions. The fundamental research questions for this project are what savings could be realized for the technology investment and what are the potential benefits of using this technology in terms of operations and maintenance. Additionally, several workshops are planned on cloud-based digital twins software and operation of IoT sensors. Both technologies have significant potential application in a modernized asset management framework, and these trainings would support talent development in the next generation of digital tools. If successful, this project would provide a blueprint for implementing this technology, at scale, to provide real-time monitoring data for modern transportation asset management.


The objective of this proof-of-technology project is to evaluate the benefits, limitations, and tradeoffs that an agency or agencies could expect when using IoT digital twin technologies for asset management, maintenance, and operations. Given the limited budget of this pilot project, the number and position of sensors will be optimized to demonstrate the potential of the technology to aid in decision-making, rather than provide a comprehensive monitoring program.


Task 1 – Trial IoT Implementation

The objective of this task is to gain familiarity with the IoT sensors that will be used in the project by deploying the IoT sensors in a controlled laboratory environment with known inputs and environmental conditions. A small number of IoT sensors will be connected to the Microsoft’s Azure IoT Hub platform, in a trial implementation of that part of the technology. It is anticipated that several different sensor types will be investigated, including:

  • Vibrating wire strain sensors for measuring anchor cable strains.
  • GPS -based positioning devices for determining the position of pontoons within the
  •  Water-level sensors to indicate when pontoons must be drained by maintenance staff.
  •  Weather stations to monitor lake conditions and correlate to other instrument
  • Tilt-sensors to monitor roll of the pontoons under light rail vehicle traffic.

For informed asset management, both long-term and transient behaviors are potentially useful and are explored in this research task. While the first four instrument types are intended for tracking long-term changes at specified time intervals (e.g., every 30 minutes), the inclination of the pontoons under vehicle loading is a transient response that requires a much higher frequency of data collection,event detection, triggering for data storage and output. The technical hurdles in collecting and retrieving both types of instrument data will be tackled in this first research task.

Task 2 – Develop Digital Twin

The objective of this task is to develop a three-dimensional digital twin model of the floating bridge that will be used to visualize IoT data, send alerts, and record long term maintenance activities. Bentley systems has developed a robust, open source iTwin.js API for integrating bridge information models, geospatial data, and sensor information. iTwin already includes built in functionality for visualizing collected data in its structural context, which will be leveraged here to provide a userfriendly interface for the engineering and maintenance crews.

The digital twin visualization will be developed, in coordination with WSDOT and technology partners, and connected to the IoT sensors being tested the laboratory before they are deployed on the physical bridge. IoT sensors and other data streams will be connected to the digital twin model using Microsoft’s Azure Digital Twins platform and Bentley systems open source iTwin.js API. Alerts and visualizations will be developed in coordination with WSDOT engineers and maintenance crews.

Task 3 – Deployment and Monitoring

The objective of this task is to investigate the location and utility of different IoT sensor types, ease of data retrieval and interpretation, integration of disparate data streams, and the ability to draw inferences pertaining to maintenance and operation decisions. The instrumentation plan for the bridge will be co-created with WSDOT engineers and maintenance crew. The proposal team has already held discussions with Mark Gaines, Nick Rodda and Patrick Clarke from WSDOT’s Bridge and Structures Office, with Brian Nielsen, WSDOT Northwest Region Administrator, and with Tom Coleman and Matthew Barber from WSP USA. The team has also met with key technology partners, including Vidhu Shekhar and Tom Miller from Microsoft, Alan Jones and David Huie from Bentley, and also Tim Johnson and Dwayne Walker, from T-Mobile.

All are supportive of the project and their valuable input has been incorporated into the current project plan. Following the development phase of the project (Task 1 and Task 2), the IoT instruments will be installed on the floating bridge and connected to the cloud through T-Mobile’s 5G network. Anchor cable instruments will be installed, with the assistance of WSDOT’s maintenance staff, who have committed their support of the proposed research plan. Following installation, data will be collected and analyzed for a period of at least nine months to capture seasonal changes.

Task 4 – Workshops

The objective of this task is to deliver training and workforce development to engineers and maintenance crews who may be considering deploying digital twin technology for asset management. Two workshops are planned:
• An introductory workshop, engaging state DOT personnel, held in collaboration with the project’s technology partners, to showcase this new technology and evaluate the most cost-effective approach to using the project resources.
• After the data collection period, a second workshop outlining the outcomes of the research program, focusing on the benefits, limitations, and tradeoffs that an agency or agencies could expect when using IoT digital twin technologies for asset management, maintenance, and operations.

Task 5 – Interim and final reporting

The research team will submit timely quarterly reports and present annually at the Research Days
meeting. Throughout the testing, the PIs will keep an open communication with the advisory panel members to make sure that the investigation is going in a direction that will be useful to the profession and to ensure rapid implementation of the results. A final report, ABC-UTC Guide, and a 5-min video presentation will be prepared that summarize the methods used and the findings reached during the project. In addition, it is anticipated that the proposed work will result in at least one journal publication.

Research Team:
Principal Investigator:  Travis Thonstad, Assistant Professor
Co-Principal Investigator: Fred Aguayo