Virtueller Gesundheitsassistent

Java desktop application that receives binary health predictions via MQTT, stores them in SQLite, computes rolling risk ratios, and visualizes the result in a dashboard with an avatar streaming view.

Documentation

• Docs Index
• Architecture
• Setup and Run
• Configuration
• Source Map
• Testing
• Known Issues

Features

• Swing desktop UI with two tabs:
• Avatar Streaming (embedded JCEF browser, default http://localhost)
• Dashboard (time series chart + problem level bar)
• MQTT client subscriber (tcp://localhost:1883) for prediction events
• SQLite persistence (data/health.db)
• Rolling ratio evaluation and automatic risk level classification:
• NONE for < 0.5
• WARNING for >= 0.5
• HIGH for >= 0.8
• DISASTER for >= 0.9
• Writes animation state JSON for Unreal integration
• Optional external process startup:
• Python MQTT simulator
• Unreal/Pixel Streaming scripts
• Custom async logger with file output + rotation

Tech Stack

• Java 17
• Maven
• Swing + FlatLaf
• JFreeChart
• Eclipse Paho MQTT
• SQLite JDBC
• JCEF (jcefmaven)
• JUnit 5 + Mockito (tests)

Runtime Flow

1. App initializes look and feel and services.
2. MQTT subscriber listens on topic from config (mqtt.topic).
3. Incoming JSON payloads are validated in BinaryEventService.
4. prediction (0/1) is stored in SQLite.
5. EvaluationService computes ratio over last 20 values.
6. AppState updates notify UI controllers.
7. Dashboard chart and status bar refresh.
8. Animation state file is written for Unreal consumption.

Payload Format

Incoming MQTT payload must be JSON like:

{
  "valid": true,
  "_id": 123,
  "prediction": 0
}

Prerequisites

• JDK 17
• Maven 3.9+
• Local MQTT broker on localhost:1883 (or adjust code/config)
• Windows environment if using bundled process scripts/paths
• Optional: Python (if MQTT simulator should be auto-started)
• Optional: Unreal + Pixel Streaming setup (path-based integration)

Configuration

Main config: src/main/resources/config/application.properties

• app.mode: current mode flag (test)
• streaming.url: initial URL for embedded stream browser
• python.path: Python executable for simulator startup
• mqtt.broker.url: MQTT broker URL
• mqtt.client.id: MQTT client id
• mqtt.topic: subscribed topic (default PREDICTION)
• mqtt_sim.enabled: start simulator process on app startup
• mqtt_sim.script: simulator script path
• animation.output.path: path for generated animation JSON file
• unreal.enabled: start Unreal-related processes
• unreal.executable: PowerShell script path for Unreal start
• unreal.signalling_server.script: signalling server batch path
• unreal.pid.file: PID file used for Unreal shutdown cleanup
• unreal.signalling.pid.file: PID file used for signalling shutdown cleanup

Logger config: src/main/resources/config/logger.properties

• logger.level
• logger.file.enabled
• logger.file
• logger.max.size.mb

Run

1) Start MQTT Broker

Start a broker on localhost:1883 (for example Mosquitto).

2) Start the App

mvn clean compile
mvn org.codehaus.mojo:exec-maven-plugin:3.5.0:java -Dexec.mainClass=vassistent.App

Or run vassistent.App directly from IntelliJ.

3) Send Test Data

Option A: enable simulator in application.properties:

• set mqtt_sim.enabled=true
• verify python.path and mqtt_sim.script

Option B: publish messages manually to topic PREDICTION.

Tests

Run:

mvn test

Current state in this repository on Java 17:

• unit and integration tests are available for state, event processing, evaluation, persistence, and statistics
• test stack uses JUnit 5 + Mockito JUnit Jupiter
• full suite runs successfully with mvn test

Project Structure

src/main/java/vassistent
  App.java
  bootstrap/      # wiring, context, shutdown sequencing
  controller/     # Swing controllers
  model/          # state + data types
  service/        # MQTT, DB, stats, evaluation, processes
  ui/             # App window, dashboard, streaming, widgets
  util/           # config + logger

src/main/resources
  config/application.properties
  config/logger.properties
  scripts/mqtt_simulator.py
  scripts/start_avatar.ps1

Important Notes

• Animation output path is now config-driven (animation.output.path).
• MQTT broker URL/client id are config-driven (mqtt.broker.url, mqtt.client.id).
• Unreal PID cleanup paths are config-driven (unreal.pid.file, unreal.signalling.pid.file).
• On app shutdown, data/health.db is deleted by App.deleteDatabase().
• The signalling server process startup in ProcessManagerService is prepared but currently not launched (pb.start() commented).