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What is Aqua-IoT?

Aqua-IoT is an Internet of Things (IoT) monitoring system designed specifically for aquaponics environments. It provides real-time monitoring of critical environmental parameters across both aquatic and plant growing zones, enabling operators to maintain optimal conditions for fish and plant health.
Aquaponics is a symbiotic system combining aquaculture (fish farming) with hydroponics (soilless plant cultivation). Fish waste provides nutrients for plants, while plants filter and clean the water for fish.

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System Overview

Aqua-IoT consists of three main components working together to collect, transmit, and visualize sensor data:

Arduino Sensors

Hardware layer with six sensor types monitoring water and environmental conditions

MQTT Bridge

Raspberry Pi running Python scripts to relay data between Arduino and cloud

Django Dashboard

Web application with REST API for data storage and visualization

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Monitored Parameters

The system tracks six critical metrics across two zones:

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Aquatic Zone (Aquarium)

  • Water Temperature: Monitored using DS18B20 digital temperature sensor
  • TDS (Total Dissolved Solids): Measures nutrient concentration in parts per million (ppm)
  • Water Level: Ultrasonic sensor measures distance in centimeters to track water levels

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Plant Zone

  • Air Temperature: DHT11 sensor measures ambient temperature
  • Humidity: DHT11 sensor tracks relative humidity percentage
  • Light Intensity: LDR (Light Dependent Resistor) measures luminosity in lumens

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Key Features

Real-Time Monitoring

Continuous sensor data collection every 2 seconds with instant MQTT transmission

RESTful API

Token-authenticated endpoints for secure data ingestion and retrieval

Historical Data

PostgreSQL database stores all sensor readings with timestamps for trend analysis

Web Dashboard

Responsive interface displaying current conditions and historical trends

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Technology Stack

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Hardware

  • Arduino: Microcontroller platform for sensor integration
  • Raspberry Pi: Edge computing device running MQTT client
  • Sensors: DHT11, DS18B20, HC-SR04 ultrasonic, TDS meter, LDR photoresistor

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Software

  • Arduino C++: Firmware for sensor reading and serial communication
  • Python 3.7+: MQTT bridge scripts using paho-mqtt and pyserial
  • Django 3.2+: Web framework with Django REST Framework
  • PostgreSQL: Relational database for sensor data storage
  • Mosquitto MQTT: Message broker for publish/subscribe messaging

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Architecture Highlights

1

Sensor Data Collection

Arduino reads six sensors every 2 seconds and outputs formatted data via serial connection
2

Serial to MQTT

Raspberry Pi reads serial data and publishes to six MQTT topics on local Mosquitto broker
3

MQTT to Django

Second Python script subscribes to MQTT topics and posts data to Django REST API endpoints
4

Data Persistence

Django models store readings in PostgreSQL with automatic timestamps
5

Visualization

Web dashboard queries database and displays real-time and historical data

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MQTT Topic Structure

The system uses a organized topic hierarchy: 
sensores/
├── temperatura-plantas   # Air temperature (DHT11)
├── umidade              # Humidity (DHT11)
├── ldr                  # Light intensity (LDR)
├── temperatura-agua     # Water temperature (DS18B20)
├── tds                  # Total dissolved solids
└── nivel                # Water level (ultrasonic)

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Use Cases

Small-Scale Aquaponics

Monitor home or educational aquaponics systems with automated alerts

Research & Development

Collect data for optimizing growing conditions and system efficiency

Commercial Operations

Scale monitoring across multiple systems with centralized dashboard

IoT Education

Learn sensor integration, MQTT messaging, and full-stack development
This project was developed for educational and monitoring purposes. For production deployment, ensure proper security configurations including changing default credentials, enabling MQTT authentication, and securing the Django SECRET_KEY.

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Next Steps

Ready to get started? Follow our quickstart guide to set up your own Aqua-IoT system, or dive into the architecture documentation to understand the technical implementation details.

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