Step 3 — Deploy the Video Player

This article refers to Platform v3.0.0. The current Platform version is v3.2.0.

warning

This step assumes the MQTT Broker and the Video Simulator are already running on the node.

Overview

The Video Player is a small web app that subscribes to a base64 video stream on the MQTT Broker and renders it on a browser page served by the edge node on port 5080. Point it at the same displayName the Video Simulator publishes to and you will see the stream.

Video Player in the pipeline

tip

Switching the Video Player between the simulator stream and the YOLOv8-annotated stream later is one config change — set deviceDisplayName to the stream you want to watch.

Add the Video Player to your Library

Video Player

Web app that subscribes to an MQTT base64 video stream and renders it in a browser.

Video Player in the Marketplace

Video Player in the App Library

Deploy the Video Player

1. Open the Node Details page and click Add card → Application.

Add card menu

Select Application

2. Select app and version. Pick Video Player and its latest version. Click Next.

Select the Video Player

3. App Secrets. Keep the defaults and click Next.

App Secrets for the Video Player

4. App Config. Paste the JSON below — deviceDisplayName must match the value set in the Video Simulator (video_simulator_01).

   {
     "video_player": {
       "system": {
         "debugLevel": "info"
       },
       "video": {
         "deviceDisplayName": "video_simulator_01"
       }
     }
   }

5. Click Send App.

Send the Video Player deployment

Verify the deployment

The Video Player workload card appears on the Node Details page. When it turns green (Started), the player is up.

Video Player workload card

Watch the stream

Open http://<NODE_IP>:5080 in a browser. The web UI starts streaming the default video published by the simulator.

warning

If your laptop is on a different network than the node, enable the VPN and use the node's VPN IP instead.

Video Player web interface

Summary

The Video Player turns the base64 MQTT stream into something a human can look at. In Step 4, you will plug Ultralytics YOLOv8 into the same pipeline and run real-time inference on every frame.