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Manage Complex Systems and Respond to Issues Faster

Track and Model Complex Transportation Systems

Today’s transportation systems need to keep track of thousands of dynamic assets, and managers have to make fast decisions when problems arise. For instance, trucking fleets need to process real-time telemetry from their vehicles, help lost or tired drivers, deal with mechanical issues, and handle traffic blockages. Airlines need to keep thousands of flights on schedule each day and rebook passengers when delays inevitably arise.

Digital twins can help these complex systems maintain a real-time picture of the huge volume of information they have to analyze. By continuously processing incoming messages, digital twins can quickly identify the most important issues in a sea of data. And digital twins can model the effects of operational changes to help managers make more informed decisions.

A Powerful Analytics Tool for Transportation Systems

Offload Managers

Transportation systems encompass a complex collection of assets in motion. Digital twins can continuously track these assets and keep operational managers informed of emerging issues.

Analyze with Context

Digital twins maintain important contextual information about each asset. As a result, they can do a better job of analyzing changes and determining when managers need to take action.

Analyze at Scale

Transportation systems generate huge volumes of real-time data. By assigning a digital twin to track each asset's data, managers can ensure that no problems go unnoticed.

Make Better Predictions

When transportation systems encounter complex challenges that threaten to derail operations, managers have to make tough decisions. Using digital twins, they can quickly run simulations to help make the right choices.

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Benefits of Digital Twins in Telematics

Faster Problem Detection: Digital twins are constantly analyzing streams of incoming data to look for emerging problems, like mechanical failures. In contrast, most of today’s telematics systems just record data to a database, where problems can go unnoticed.

Deeper Insights: Digital twins use state information to add context to the telemetry they are analyzing and enable deeper insights. For example, when they analyze the unexpected lateral acceleration of a vehicle, they can factor in the driver’s time behind the wheel and past accident history.

Better Situational Awareness: Instead of waiting for delayed offline analysis, managers can aggregate and visualize data from digital twins, such as on-time performance and fuel efficiency, to track overall fleet performance. This capability helps managers maintain the big picture at all times and make better decisions.


Airline passengers per day


Commercial vehicles sold worldwide in 2022


Freight rail cars in the U.S.

Implementing Digital Twins in Transportation Systems

When doing real-time analytics, digital twins can track live assets in a transportation system, such as the vehicles in a fleet or the planes of an airline. They hold important information about these assets that helps make sense of incoming telemetry and identify issues.

For example, digital twins can help prevent derailments in a nation’s freight rail system by analyzing telemetry from rail-side detectors. By looking for patterns across many detectors, these digital twins can raise an alert when they predict a pending failure.

Digital twins also can assist in decision-making for transportation systems, such as airlines, by implementing simulation models. Operational managers can use these models to evaluate alternative decisions that help resolve issues and optimize operations.

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