PROJECT ENGINEERING
Multi-camera video, GPU inference and spatial results in a complete edge application.
The platform connects camera streams, image processing, inference, event association and spatial analysis with an embedded HTTP service and host tools. Operators can manage parameters and calibration assets, inspect results and observe runtime health.
The implementation uses NVIDIA Jetson, CUDA-assisted processing and TensorRT neural-network inference, with batch processing across camera channels. Traditional image analysis and neural detections contribute to event processing through explicit camera and frame identities.
Camera calibration and scene geometry support monocular and stereo localisation paths. Cross-camera event association and historical observations let the application retain the relationship between a detection, its input images and the geometry used for analysis.
Processing, inference and result delivery have separate execution boundaries. Bounded queues, retries, optional persistent delivery, health reporting and release-package checks support controlled operation and handover. These are implemented engineering mechanisms, not a claim of independently certified availability or field accuracy.
05 / LET’S BUILD SOMETHING
Tell us what you want to build.
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