Live Streaming
Building Real-time Video Streaming with AI Enhancement
Implement low-latency streaming pipelines with AI features like auto quality and moderation.
A
Alex Chen
2024-01-15 • 8 min read
Overview
Delivering live video at scale requires managing latency, quality, and reliability. In this guide we design an end-to-end pipeline from ingest to playback, adding AI for automatic bitrate selection and content moderation.
Pipeline
We use an RTMP/WebRTC ingest, a transcoding stage, an origin, and a global CDN. We measure effective latency (glass-to-glass) and use QoS events to adapt.
{"{ \"ingest\": \"WebRTC\", \"codec\": \"H.264\", \"profile\": \"baseline\" }"}AI Moderation
Frames are sampled for inference. We run a lightweight model to detect sensitive content and apply policy-driven actions without blocking the main stream.
Takeaways
- Use ABR for adaptive quality
- Emit client QoS beacons every 2s
- Moderate asynchronously with backpressure