FreeScopes AI enables engineers to build and deploy AI for radar and sensor data without coding. A short demonstration shows rapid object classification in practice.
Artificial intelligence is increasingly essential in radar and sensor-based environments, yet implementing AI in operational systems often requires complex software development and specialised data-science expertise. FreeScopes AI was designed to close this gap.
FreeScopes AI is a no-code engineering platform that allows radar engineers and system specialists to design, train, validate, and deploy AI models directly within their operational workflow. Instead of building custom pipelines in external frameworks, users assemble neural networks through a visual interface, connect datasets, train models, and immediately test results inside the same environment.
The platform integrates the full lifecycle of applied AI:
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data acquisition,
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preprocessing,
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model configuration,
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training, validation,
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and deployment.
The objective is to transform AI from a specialised software activity into a practical engineering capability for radar, ISR, and sensor-based systems.
Demonstration: Classifying Radar Targets with FreeScopes AI I
In the short video below we demonstrate the workflow of FreeScopes AI I, the entry module of the FreeScopes AI platform.
Three objects were used for the experiment:
- a small sphere
- a large sphere
- a corner reflector
Radar measurements were first recorded using the FreeScopes environment. These datasets were then imported into the FreeScopes AI interface, where the neural network architecture was assembled visually using drag-and-drop building blocks.
The AI chain consisted of an input layer, dense neural network layers, and a training module. The configuration was completed in seconds—without writing a single line of code.
After training, the model was validated using additional measurement data. The resulting classifier successfully distinguished between the three radar targets with 100% accuracy in the test dataset.
This example illustrates how quickly radar engineers can move from raw measurements to a functional AI model within the FreeScopes environment.
From AI Implementation to Cognitive Radar
The next step, FreeScopes AI II, expands these capabilities toward advanced experimentation, including simulated jamming scenarios, adaptive model optimisation, and AI-supported counter-countermeasure development.
Beyond these stages, the medium and long-term development direction of the platform which aims to support experimentation with cognitive radar and cognitive electronic warfare concepts. In such systems, AI models do not only analyse signals but contribute to adaptive sensing strategies and spectrum awareness.
The broader objective is to provide an engineering environment in which radar specialists can explore learning-based detection, multi-sensor fusion, and adaptive spectrum interpretation in a controlled and reproducible way.
Developed and financed in Luxembourg, FreeScopes AI demonstrates how advanced applied AI for radar and electromagnetic environments can be implemented as a practical engineering tool. The platform is already used in military AI implementation training and research contexts and is being expanded through collaborations in European innovation programmes.
By enabling domain experts—not only data scientists—to design and deploy AI models directly within radar workflows, FreeScopes AI contributes to the transition from traditional signal processing toward adaptive, learning-driven radar and spectrum technologies.
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