GeoWatch

Interface for location, monitoring and controlling devices

Your Docker Compose architecture is designed to facilitate a constant data flow from sensor devices (like ESP32) to a backend system, where data is processed and stored in a PostgreSQL/PostGIS database. The following outlines the key components and their interactions based on your provided configuration:

Architecture Overview

1. Sensor Devices

Function: These devices act as data sources, sending their schema and sensor data via MQTT.
Data Flow:
- Schema sent to: /box/boxname/schema
- Sensor data sent to: /box/boxname/data

2. MQTT Broker

Service: mqtt
Image: eclipse-mosquitto
Role: Acts as the messaging hub for receiving data from sensors and distributing it to the backend service.
Ports: Exposes port 1883 for MQTT communication.

3. Backend Service

Service: backend
Build Context: Located in ./backend
Role:
- Subscribes to MQTT topics to receive sensor data.
- Processes and saves this data into the PostgreSQL database.
Environment Variables:
- Configured with MQTT broker details and database credentials.

4. PostgreSQL with PostGIS

Service: db
Image: postgis/postgis
Role:
- Stores geospatial data and sensor readings.
- Allows for advanced queries on spatial data.
Volumes: Persists data in a defined volume.

5. Grafana

Service: grafana
Image: grafana/grafana
Role: Visualizes the data stored in PostgreSQL.
Ports: Exposes port 3000 for web access.
Plugins Installed: Includes various plugins for enhanced visualization capabilities.

6. Streamlit

Service: streamlit
Build Context: Located in ./frontend
Role: Provides an interactive web application for displaying device locations and statistics.
Ports: Exposes port 8501 for user access.

Data Flow Diagram

[ESP32 Sensors] --(MQTT)--> [MQTT Broker] --(Data)--> [Backend]
         |                          |                      |
         |                          |                      |
         +------------------------->+                      |
                                 (Schema)                |
                                                       [PostgreSQL]
                                                         |
                                                         |
                                                      [Grafana]
                                                         |
                                                      [Streamlit]

Key Features

Real-time Data Processing: The architecture allows for immediate processing of incoming sensor data through the backend service.
Geospatial Capabilities: Using PostGIS enables advanced geospatial queries, making it suitable for applications in precision agriculture and environmental monitoring.
Visualization Tools: Grafana and Streamlit provide robust platforms for visualizing and interacting with the collected data.