AgroPi

Cultivate your plants and mushrooms with ease through a Raspberry Pi driven monitoring and controlling system.

Contents

1. About
   • Software
   • Hardware
   • Roadmap
2. Getting Started
   • Prerequisites
   • Installation
   • Usage
3. Contributing
4. License
5. Contact

About

AgroPi is a flexible modular monitoring and actuating tool which allows user to control enviroment within a small chamber to provide the desired conditions for mushroom and plant cultivation. It is up to the user to decide what actuators fit the enviromental chamber needs best as the main swiching technology utilizes GPIOs controlling relay board.


Website interface enables user to easily display and control the conditions within enviromental chamber in real time. In addition AgroPi takes photos of your growth in constant intervals so you can show off your crops.

• Tutorial

Software

v0.2 Release allows you to view the following conditions on the website interface:

• Temperature
• Humidity
• Light Intensity
• TVOC
• eCO2
• Ethanol
• Hydrogen

Dashboard

As well as easily set the target values for your environmental chamber.

Control Panel

Camera also allows for basic seedlings detection

Control Panel

See Doxygen Documentation

Hardware

Raspberry Pi 4 Model B

Sensors:

• Raspberry Pi Camera Rev 1.3 Lens: P5V04A, Cable: AWM 20624
• Thermometer + Humidity - SHT31D
• Light - VEML7700
• Gas - SGP30

Actuators - This is your choice as AgroPi is designed to control relay by changing state of the GPIO pins(make sure your relay module is compatible with 3v3 logic). For our demo the following are used:

Switching Technology:

• Relay Board - Elego

Actuators:

• Heating Element - Zerodis PTC Heating Element AC/DC 12V (80 ℃ 2—5W)
• Water Pump
• Fan - Coolermaster A12025-12CB-3BN-F1

Schematics:

• System Schematic

Example Setup

Roadmap

[x] Next Software Release (v0.2) - Actuation & Image Processing - Detecting Seedling/Mushroom - 20/04/2021

• Camera Integrated
• Relay Board Driver
• Relay Board Integration
• Web-Server Improvments
• Gather Training Dataset
• Train neuralnet
• Test on real samples

[] Software Release 3 Planning scheduled for september 2021(v0.3)

Getting Started

Prerequisites

1. Clone the repository

git clone https://github.com/krogk/AgroPi

2. Ubuntu Packages:

chmod +x install.sh
./install.sh

3. Server Depencencies:

pip install -r requirements.txt

Installation

1.Build:

mkdir build
cd build/
cmake ..
make test ARGS="-V"  <- Optional Test Run, All sensors must be connected
make

2. Point Nginx File to AgroPi static website, modify the contents of /etc/nginx/sites-enabled/default

server {
        listen       80;
        server_name  localhost;

        location /favicon.ico {
          return 204;
          access_log     off;
          log_not_found  off;
        }

        location /sensor/ {
          include        fastcgi_params;
          fastcgi_pass   unix:/tmp/fastcgisocket;
        }

        location / {
          root pathToAgroPi/AgroPi/software/web/html;
          index dashboard.html;
        }

        location /static/ {
               root pathToAgroPi/AgroPi/software/web/app;
        }
}

Usage

To run the software:

1. Go to build directory and run application

./src/AgroPi 

2. Wait 15 Seconds for application to set up sensors.

3. Connect to webiste in your browser on your phone or pc

 (Rpi ip adress):80

4.Switch to control pannel, update your target values and enable your actucation heuristics.

Contributing

See CONTRIBUTING for more information.

License

Distributed under the GPL-3.0 License. See LICENSE for more information.

Contact

Samuel Obosu - Web server & Network Programming
Andrew Scott-George - Image Processing, 3D design, & PR
Kamil Rog - C++ Real-time Embedded Programming