🌱 Raspberry Pi Automatic Hydroponic System

This repository contains a Python script to manage and monitor an automatic hydroponic system using a Raspberry Pi 4. The code takes care of various tasks, such as priming pumps, filling water, dosing nutrients, and balancing pH levels.

✨ Features

• Automatic water management with user-inputted target water level, and dry-back function using a water level change threshold
• Nutrient dosing with target PPM (parts per million) and safety margin
  • There are three commonly used conversion factors for TDS meters: 500, 640, and 700
  • These all convert the EC value and the choice depends on the source of the nutrient solution
  • The 500 scale is the most common conversion factor and is typically used for nutrient solutions made with reverse osmosis or distilled water (Default for this system)
• pH management with up pump and down pump control
• Logging system to keep track of the hydroponic system's status
• Storage of different plant customization of settings, including pH, max water level, dryback (how low can the water get before a refill), starting ppm, etc to easily switch control from one plant to another
• Error handling and pump stopping in case of exceptions

📦 Requirements

• Python 3.7 or higher

(~Estimated) Parts under $20

• Zip ties: $4 - $6
• Wire stripper: $6 - $10
• 12V AC adapter (2x): $6 - $10
• Raspberry Pi Cobbler: $6 - $10
• Heat shrink pack: $6 - $10
• Epoxy glue: $8 - $12
• Wood board: $8 - $12
• Mason jars: $8 - $12
• Raspberry Pi screw set: $8 - $12
• Long screws for pump attachment: $8 - $12
• Silicone tubing: $8 - $12
• Temperature sensor and circuit: $8 - $12
• Analog-to-digital converter: $10 - $12
• Protoboards: $12 - $18
• Large fresh water pump: $12 - $18
• Multistrand wire pack: $13 - $20
• Single strand wire pack: $13 - $20
• Wire crimper and crimps: $15 - $25

(~Estimated) $20 - $50

• Clear PVC tubes (4x): $20 - $30
• 8-gallon bucket with lid: $25 - $35
• pH probe Voltage isolator (Atlas Scientific): $25 - $35
• EC probe Voltage isolator(Atlas Scientific): $25 - $35
• Water level sensor (E-Tape): $30 - $50
• IOT Relay (RPI-controlled power strip): $30 - $50

(~Estimated) Over $50

• EC probe (Atlas Scientific): $35 - $55
• pH probe (Atlas Scientific): $40 - $60
• Peristaltic pumps (7x): $60 - $90
• Soldering Iron kit: $65 - $95
• Raspberry Pi B+: $100 - $140

Total estimated cost range: $600-$900

🛠️ Installation

1. Clone this repository to your Raspberry Pi:

git clone https://github.com/HydroLB/automatic-hydroponic-system.git

2. Navigate to the project folder:

cd RPI_Auto_Hydroponics

3. Install the required packages using pip:

pip install -r requirements.txt

⚙️ Configuration

You will need to configure the following variables in the main function code:

• ph_var: List of 3, containing times for pH up and down pumps to be on per cycle, and time between each cycle (loop) when dosing for pH.

• WATER_LEVEL_CHANGE_THRESHOLD: This parameter determines the minimum difference in water level (in inches) needed to trigger a fill-up, promoting stronger root growth by encouraging plants to search for water deeper in the ground. Adjust the threshold to optimize watering frequency and root strength. Consider updating this value in relation to the plant's growth stage. As the plant matures, increase the time between fill-ups to encourage deeper root growth.

• Smaller threshold -> More frequent fill-ups. Larger threshold -> Less frequent fill-ups, stronger roots. Never let the roots be too dry. I rather err on the side of caution even if the roots won't be as big.

• WAIT_TIME_BETWEEN_CHECKS: Time in seconds to wait between each water level check and ph check.

• NUTRIENT_PPM_SAFETY_MARGIN: Safety margin in ppm between the actual target PPM and the first nutrient dosing cycle, as the ph balancing raises ppm too.

🚀 Usage

1. Run the main script to start the automatic hydroponic system:

python3 main.py

2. Follow the prompts to reset and prime the pumps and input the target PPM and water level for your system.

3. The script will continuously monitor the hydroponic system and make adjustments as necessary based on the plants response.

📝 Notes

• Ensure that your pumps and sensors are properly connected to the Raspberry Pi before running the script.
• The code is designed to work with a specific set of pumps and sensors. You may need to modify the code to work with different hardware.
• The water level, and PPM are stored in a file to allow the system to resume its monitoring in the event of a reboot or power outage.

🤝 Contributing, credits and special thanks:

Special thanks to Michael Yinka-Oke and Sean Cunneen for bringing this project and idea to from the ground to reality!

This project was developed using a variety of tools, including PyCharm as the integrated development environment and implemented on a Raspberry Pi platform.

📄 License for code:

This original work is licensed under the GNU Affero General Public License v3.0 (AGPLv3). The full license text can be found at https://www.gnu.org/licenses/agpl-3.0.en.html

Original contributions and unique code in this project: Copyright © 2023, Leon Bouramia. All rights reserved.

Contributions are welcome! If you have any suggestions or improvements, feel free to submit a pull request or create an issue.

🌟 Ideas to Add to the Future:

1. Alerts and Notifications: Add a feature for sending alerts and notifications when certain conditions are met or thresholds are exceeded, such as low water levels, pH imbalances, or high nutrient concentrations. This will keep you informed about your system's status and help you react promptly to any issues.

2. Data Visualization: Enhance your project by adding a feature for visualizing logged data, such as water level at certain times, pH levels, and nutrient levels, over time. This will enable you to analyze your hydroponic system's performance and make necessary adjustments.

3. Web/Mobile Interface: You may want to develop a web or mobile application for interacting with the Raspberry Pi and controlling the hydroponic system. This will provide you with the ability to remotely monitor and manage your plants.

4. Light Management: Incorporate a light management system to control light intensity and duration, simulating day-night cycles and optimizing plant growth.

5. Camera Integration: Consider integrating a camera module with your Raspberry Pi to enable visual monitoring of plant growth and health. This will allow you to track your plants' progress using a timelapse.

6. Temperature Control: Implement a new temperature sensor to control a heater or cooler to maintain optimal temperature levels in the hydroponic environment. This will ensure that your plants grow in the most suitable conditions.

7. Humidity Control: Implement a humidity sensor and control system (fans) to maintain optimal humidity levels in the hydroponic environment.