OverviewAbout this program
Modern edge devices are multimedia machines first. A smart camera, an automotive ECU, a medical imaging unit or an industrial vision system all live or die on one thing: how cleanly frames and audio flow from silicon to software to AI. This program takes you deep into the Linux kernel subsystems that make that flow possible — and shows you how to engineer them for real, shipping products.
You'll work through the complete multimedia driver stack: the V4L2 framework and media controller that model capture pipelines, camera sensor and ISP sub-devices, the DRM/KMS display path, the ALSA audio subsystem and hardware video codecs. Every layer is taught from the driver author's perspective — buffers, formats, sub-device graphs, controls and the DMA infrastructure underneath.
The defining theme is edge AI. A captured frame is only useful when it reaches an inference engine efficiently. You'll learn to move frames zero-copy across the pipeline, hand them to accelerators and close the loop into real-time on-device vision. The methodology is learn-by-doing: every concept is paired with a lab on real hardware, building from fundamentals to a full capture-to-AI pipeline.
OutcomesWhat you'll be able to do
- ✓ Read, write and debug V4L2 drivers and understand the full capture data path end to end.
- ✓ Model real capture pipelines with the media controller framework and sub-devices.
- ✓ Bring up camera sensors over CSI-2 and reason about the ISP and image tuning.
- ✓ Manage video buffers and frame memory with videobuf2 and DMA-BUF.
- ✓ Drive displays through the DRM/KMS subsystem — planes, CRTCs and overlays.
- ✓ Work with the ALSA audio stack and synchronise audio with video.
- ✓ Integrate hardware video codecs for encode and decode, including stateless decode.
- ✓ Build zero-copy, low-latency pipelines that feed frames to edge-AI inference.
- ✓ Assemble end-to-end capture-to-AI pipelines and tune them for throughput and latency.
- ✓ Profile, trace and debug multimedia drivers in production-grade systems.
