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edge-media-agent

Implement an edge-native video pipeline with RTSP/SRT/WebRTC/ONVIF ingestion and on-device processing.

Updated Apr 4, 2026
Search Tags:#video#pipeline#ffmpeg#inference#onvif#edge#gstreamer
One-click install
npx skills add https://github.com/asalhamed/dev-agents --skill edge-media-agent
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: edge-media-agent
Source: https://github.com/asalhamed/dev-agents/tree/main/edge-media-agent
Command: npx skills add https://github.com/asalhamed/dev-agents --skill edge-media-agent

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Implement a robust edge-native video pipeline that ingests camera streams, performs on-device processing, and coordinates bandwidth-aware cloud sync, enabling operation with intermittent connectivity and privacy-preserving edge analytics.

Core Features & Use Cases

  • Ingest from RTSP, SRT, WebRTC, and ONVIF-discovered sources with low latency and local buffering.
  • On-device processing: transcoding, CV inference, motion/alert triggers, and selective data forwarding to the cloud.
  • Adaptive streaming and store-and-forward: support live viewing (WebRTC/HLS) and local recording while optimizing bandwidth.
  • Edge deployment patterns: runs on K3s/MicroK8s with bounded resources; designed for offline operation.

Quick Start

Run the edge-media-agent on your edge node to initialize camera ingestion, local processing, and cloud sync with the configured pipelines.

Frequently Asked Questions about edge-media-agent

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build an edge video pipeline for low-latency RTSP ingestion and on-device inference?▼

To build an edge video pipeline, launch edge-media-agent to ingest RTSP streams and perform on-device CV inference. It manages low-latency local buffering and processing directly on your edge hardware.

What is store-and-forward cloud sync for video pipelines under bandwidth constraints?▼

Store-and-forward cloud sync is a mechanism that locally records video streams and selectively forwards data to the cloud when bandwidth allows. It ensures bounded storage and prevents data loss during intermittent connectivity.

Can I run video processing and transcoding on K3s or MicroK8s with bounded resources?▼

Yes, you can run video processing and transcoding on K3s or MicroK8s with bounded resources. The pipeline is designed for edge deployment patterns supporting offline operation and constrained environments.

Does ONVIF camera discovery work with WebRTC and SRT ingestion for adaptive streaming?▼

Yes, ONVIF camera discovery works alongside RTSP, SRT, and WebRTC ingestion. The pipeline supports adaptive streaming for live viewing via WebRTC or HLS while optimizing overall bandwidth.

How do edge video pipelines handle hardware acceleration and model version traceability?▼

Edge video pipelines handle hardware acceleration and model version traceability by satisfying edge autonomy requirements during on-device processing. This ensures consistent CV inference execution and tracked model deployments.

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