IoT Sensor Data Collection and Visualization System

Table of Contents

1. Overview
2. System Architecture
3. Setup Instructions
   • Installing Dependencies and Running the System
4. Documentation
   • Technologies Used
   • Code Documentation
   • Decision Documentation

Overview

This project simulates the collection of temperature and humidity data from various sensors. The data is aggregated by hubs, sent to a server via MQTT, stored in InfluxDB and PostgreSQL, and displayed using a React-based web dashboard.

System Architecture

The system is composed of the following key components:

• Simulated Sensors: Generate random temperature and humidity data.
• Hubs: Collect data from sensors and publish it to an MQTT broker.
• MQTT Broker: Facilitates communication between hubs and the server.
• Server: Subscribes to MQTT topics, processes incoming data, and stores it in InfluxDB.
• Database: InfluxDB to store time-series data and PostgreSQL to manage user data and authentication.
• Data Visualization: A React-based dashboard to visualize the collected sensor data.

Setup Instructions

Installing Dependencies and Running the System

1. Backend (Python and PostgreSQL and MQTT Broker and InfluxDB)

   docker-compose up

2. Frontend (React)

   cd dashboard
   npm install
   npm start

Documentation

Technologies Used

• Python: For simulating sensors and hubs, and for the FastAPI web server.
• MQTT (Mosquitto): For data communication.
• FastAPI: For developing the web server.
• InfluxDB: Ideal for time-series data storage and you can access to its UI dashboard via localhost.
• PostgreSQL: Robust database for storing user authentication data.
• React: Preferred for its component-based architecture and dynamic UI capabilities.

Code Documentation

• Hub Simulator (Python):

  • Simulates sensors generating random data.
  • Publishes data to MQTT topics.

• FastAPI Server:

  • Subscribes to MQTT topics.
  • Processes and stores data in InfluxDB.
  • Provides REST endpoints to fetch data for visualization and hub ids.
  • User registration and authentication using PostgreSQL.
  • You can access documentation and schemas via docs.
  • And there is a postman API Collection that you can import and use.
  • Provides a web-socket api to stream hubs data real-time.

• React Dashboard:

  • Fetches sensor data and hub ids from the FastAPI server.
  • Visualizes data using Chart.js (react-chartjs-2).
  • Visualizes Real-Time Chart using web socket and you can choose between them.
  • Advanced Data Filtering by date and time and hub ids and you can have all your hub data in just one chart.
  • Provides user login interface.
  • Uses Material UI to enhance the UI.
  • You can access it via localhost after npm start.

Decision Documentation

• Technology Choices:
  • MQTT: Chosen for its lightweight, reliable messaging suited for IoT scenarios.
  • FastAPI: Selected for its fast performance, ease of use, and modern Python support.
  • InfluxDB: Ideal for time-series data storage with efficient querying.
  • PostgreSQL: Robust and reliable for user data and authentication.
  • React: Preferred for its component-based architecture and dynamic UI capabilities.

Sample Chart Example