A crop monitoring system made using a Raspberry Pi 4B, a 7-in-1 NPK sensor, an ultrasonic sensor, and an ESP32 Wi-Fi module.

• Real-time Soil Monitoring: pH, moisture, temperature, conductivity, nitrogen, phosphorus, potassium (NPK)
• Plant Growth Tracking: Ultrasonic distance sensor for growth rate calculation
• WiFi Connectivity: ESP32 module provides WiFi access to Raspberry Pi
• Cloud Integration: Data stored in Firebase Firestore
• Telegram Notifications: Real-time alerts and data reports
• Automated Scheduling: Data collection at configurable intervals (8-10 AM, 12-2 PM, 8-10 PM)

• Raspberry Pi 4B
• 7-in-1 NPK Soil Sensor (RS485)
• HC-SR04 Ultrasonic Distance Sensor
• ESP32 WiFi Module
• USB to RS485 Converter

pip install -r requirements.txt

Or manually:

pip install python-dotenv RPi.GPIO pyserial geocoder requests firebase-admin pyTelegramBotAPI telethon google-cloud-firestore

1. Copy the example environment file:

   cp .env.example .env

2. Edit .env and fill in your actual configuration:

   • Firebase credentials and API key
   • Telegram API credentials
   • Serial port settings
   • Location and plant IDs

1. Navigate to the wififile directory:

   cd wififile

2. Copy the config template:

   cp config.h.example config.h

3. Edit config.h and add your WiFi credentials:

   const char* WIFI_SSID = "your_wifi_ssid";
   const char* WIFI_PASSWORD = "your_wifi_password";

1. Open wififile.ino in Arduino IDE
2. Select your ESP32 board (Tools → Board → ESP32 Dev Module)
3. Select the correct port (Tools → Port)
4. Upload the sketch

The ESP32 accepts the following commands from Raspberry Pi over serial:

On the Raspberry Pi:

python CMPEProject.py

The system will:

• Connect to Firebase and authenticate
• Monitor soil conditions every 24 minutes (5 readings per collection window)
• Calculate and send average readings to Firestore
• Send notifications via Telegram
• Track plant growth rate using ultrasonic sensor

Security Note: Never commit .env, config.h, or serviceAccountKey.json to version control.

This website is part of the MoniCrop Smart Crop Monitoring System:

• MoniCrop Website - Functional Website
• MoniCrop iOS App - Mobile application for iOS

If you use this work, please cite:

@article{Afi2023,
  author = "Eman Sarah Afi",
  title = "{Development of a Smart Crop Monitoring System}",
  year = "2023",
  month = "10",
  url = "https://aubh.figshare.com/articles/thesis/_b_Development_of_a_Smart_Crop_Monitoring_System_b_/30580751",
  doi = "10.58014/aubh.24314056.v2"
}

Published thesis: Development of a Smart Crop Monitoring System (DOI: 10.58014/aubh.24314056.v2)