Hydroponics Monitoring and Control System

Overview

This project is a smart hydroponics monitoring and control system that integrates Django with MySQL to store and manage sensor data. The system uses machine learning (LSTM and other techniques) to predict water quality, schedule sensor calibration and maintenance, and provide automated control of actuators.

Features

• Sensor Data Collection: Data from multiple sensors across different locations (Greenhouse, Water Test Bed, Water Bed, Water Bio Filter, and Fish Tank) are collected and stored in MySQL.
• Alerts & Notifications: The system triggers alerts for:
  • Sensor calibration and maintenance needs.
  • Water quality deviations.
• Data Visualization: Display sensor data using tables and charts.
• Machine Learning Predictions: LSTM-based predictions for:
  • Water quality trends.
  • Sensor maintenance schedules.
• User Management:
  • Admin: Can manage sensors, users, and control devices.
  • User: Can register, log in, and view sensor data.
• Device Control: Ability to turn devices ON/OFF based on sensor conditions.

Components

Hardware

Sensor Panel

• Collects data from multiple sensors using RS485 communication.
• Sends data to MySQL via RS485 to USB converter.

Actuator Panel

Devices controlled by the system:

1. EXHAUST FAN
2. WATER PUMP
3. WATER BLENDER
4. EVAPORATOR COOLER
5. AERATION PUMP
6. SOLENOID VALVE 1
7. GREENHOUSE LIGHT
8. FISH FEEDER
9. SOLENOID VALVE 2
10. NAIMER LAMPS
11. SOLENOID VALVE 3
12. GREENHOUSE SHADING
13. WATER AERATOR
14. SOLENOID VALVE 4

Main Panel

• Uses Jetson Nano for data processing.
• A 7-inch LCD Display provides a graphical interface.
• 10-Port USB Hub for device connectivity.
• Power managed via 220VAC Power Distribution Unit.

Software Stack

• Django (Backend): Handles user authentication, sensor data storage, and control logic.
• MySQL (Database): Stores sensor readings, user data, and device states.
• Machine Learning: LSTM and other models predict water quality and maintenance needs.
• JavaScript (Frontend): For interactive charts, tables, and control buttons.
• Bootstrap & DataTables: Enhances UI for data presentation.

Installation

1. Clone the Repository

  git clone https://github.com/llenny18/hydroatlantis.git
  cd hydroatlantis

2. Install Dependencies

  pip install -r requirements.txt

3. Run Database Migrations

  python manage.py migrate

4. Start the Django Server

  python manage.py runserver

Usage

• Login/Register as an Admin or User.
• View sensor data in tables and charts.
• Receive alerts for water quality and sensor issues.
• Control devices remotely from the dashboard.

Contributors

• Digital Transformation Center - Developer & Researcher