Built around real airfield vehicle operations.
Training environments are designed to reflect real operational conditions, including:
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Snow-covered runways and plowed corridors
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Reduced visibility and night operations
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Runway and taxiway proximity awareness
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Ground vehicle behavior under changing surface conditions
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Familiarization with active airfield layouts
Airside Driver Training Safety Simulation
3D Virtual Model of Your Airfield
A scalable simulation environment designed for airside vehicle operations, helping airports improve operator familiarity, spatial awareness, and operational readiness before entering active movement areas.
Supporting operational readiness.
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Improve airside familiarization
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Reduce reliance on live operational training
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Support more consistent operator preparation
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Improve spatial awareness in active movement areas
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Expand access to realistic training environments
Bringing realistic airfield familiarization to more operators.
Request a demonstration to see how the InspectEx training environment supports scalable airfield driver familiarization and operational readiness.
Having a highly detailed virtual airfield model in Unreal Engine serves as the foundation for a wide range of training and simulation applications. Using automation, AI-driven feature extraction, and eventually neural reconstruction powered by our InspectEx platform, we can accelerate the creation of accurate, high-fidelity digital airfields.
Other Use Cases
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Operations Planning:
Use the digital twin to support maintenance scheduling, resource allocation, and inspection planning with a continuously updated, spatially accurate view of the airfield. Teams can evaluate current conditions and plan activities with greater situational awareness.
Scenario Analysis:
Model and evaluate potential operational scenarios such as construction, closures, environmental impacts, or emergency events. The digital twin allows teams to assess outcomes in advance, helping improve preparedness and reduce operational risk.
Data Visualization & Analysis:
Aggregate inspection data, sensor inputs, and AI detection outputs into a unified 3D environment. The digital twin enables users to visualize airfield conditions spatially, analyze trends over time, and identify patterns that support informed decision-making.