Introduction to Smart Agriculture with Automated Drone Control

In modern agriculture, smart farming technologies play a crucial role in improving crop yield and reducing the environmental impact of farming activities. This project demonstrates how to create an automated Smart Agriculture system using an ESP32 microcontroller that collects data from various environmental sensors and controls a drone for automated tasks like crop monitoring, spraying, and data collection. The system provides real-time data to farmers and can make automatic decisions based on sensor readings.

Components Required

To build the ESP32-powered Smart Agriculture System, you will need the ESP32 development board, environmental sensors (soil moisture, temperature, humidity), a drone compatible with Arduino/ESP32 for control, Wi-Fi connectivity, a power source, and a cloud platform for data visualization.

• Set up the ESP32 development environment with necessary libraries for drone control and sensors.
• Connect environmental sensors (soil moisture, temperature, humidity) to the ESP32.
• Set up a Wi-Fi connection for sending data to a cloud service (e.g., ThingSpeak, AWS IoT).
• Integrate the drone control system with ESP32 for automated actions (e.g., flying, spraying, data collection).
• Write code to read data from sensors and send it to the cloud.
• Program automated flight paths for the drone based on sensor readings (e.g., low moisture levels trigger drone watering).
• Visualize real-time data and drone status on a dashboard or mobile app.

Formula: Smart Agriculture Efficiency = (Real-Time Data Collected / Tasks Automated) * 100

Components List

• 1 × ESP32 Development Board
• 1 × Soil Moisture Sensor (e.g., Capacitive Soil Moisture Sensor)
• 1 × Temperature Sensor (e.g., DHT22)
• 1 × Humidity Sensor (e.g., DHT22)
• 1 × Drone (e.g., DJI, DIY drone with ESC, motors, and controller)
• 1 × Wi-Fi Module (ESP32 has built-in Wi-Fi)
• 1 × Power Supply (e.g., 5V adapter for ESP32, Li-Po battery for drone)
• 1 × Cloud Service (e.g., ThingSpeak, AWS IoT, MQTT Broker)

Pin Configuration

• GPIO 34 (Soil Moisture Sensor): Soil moisture sensor connected to GPIO 34 of the ESP32.
• GPIO 35 (Temperature Sensor): Temperature sensor connected to GPIO 35 of the ESP32.
• GPIO 32 (Humidity Sensor): Humidity sensor connected to GPIO 32 of the ESP32.
• GPIO 33 (Drone Control Pin): Control pin connected to the drone's motor controller (ESC) for controlling drone movements.

For drone control, ensure the drone is compatible with ESP32 or Arduino-based flight controllers, and the flight controller accepts PWM signals for movement control.

Wiring and Connections

• -> GPIO 34 (Analog input)
• -> GPIO 35 (Digital input)
• -> GPIO 32 (Digital input)
• -> GPIO 33 (PWM output for motor control)

Code for ESP32-Based Smart Agriculture System with Automated Drone Control

1#include <WiFi.h>
2#include <PubSubClient.h>
3#include <DHT.h>
4#include <Servo.h>
5
6const char* ssid = "Your_SSID";
7const char* password = "Your_PASSWORD";
8const char* mqttServer = "mqtt_broker_address";
9const int mqttPort = 1883;
10
11WiFiClient espClient;
12PubSubClient client(espClient);
13DHT dht(35, DHT22);
14Servo droneMotor;
15int soilMoisturePin = 34;
16int soilMoistureValue = 0;
17
18void setup() {
19  Serial.begin(115200);
20  WiFi.begin(ssid, password);
21  while (WiFi.status() != WL_CONNECTED) {
22    delay(1000);
23    Serial.println("Connecting to WiFi...");
24  }
25  Serial.println("Connected to WiFi");
26  client.setServer(mqttServer, mqttPort);
27  dht.begin();
28  droneMotor.attach(33); // Attach motor to GPIO 33
29}
30
31void loop() {
32  if (!client.connected()) {
33    reconnect();
34  }
35  client.loop();
36  soilMoistureValue = analogRead(soilMoisturePin);
37  float temperature = dht.readTemperature();
38  float humidity = dht.readHumidity();
39  String payload = "Soil Moisture: " + String(soilMoistureValue) + " Temperature: " + String(temperature) + " Humidity: " + String(humidity);
40  client.publish("agriculture/data", payload.c_str());
41
42  // Automated drone control based on soil moisture
43  if (soilMoistureValue < 500) {
44    Serial.println("Low moisture detected, activating drone.");
45    droneMotor.write(90); // Activate drone motor to start watering
46    delay(5000); // Keep motor on for 5 seconds
47    droneMotor.write(0); // Stop motor
48  }
49
50  delay(2000); // Delay for the next loop
51}
52
53void reconnect() {
54  while (!client.connected()) {
55    if (client.connect("ESP32Client")) {
56      client.subscribe("agriculture/data");
57    } else {
58      delay(5000);
59    }
60  }
61}

Code Explanation

• #include <WiFi.h>: This line includes the Wi-Fi library to connect the ESP32 to a wireless network, enabling cloud communication.
• PubSubClient client(espClient);: This initializes the MQTT client, which allows the ESP32 to send data to an MQTT broker for real-time monitoring.
• droneMotor.attach(33);: This attaches the drone motor control to GPIO pin 33 of the ESP32. The motor will be controlled by PWM signals sent through this pin.
• soilMoistureValue = analogRead(soilMoisturePin);: This reads the soil moisture sensor value from the analog pin (GPIO 34) to determine if watering is needed.
• droneMotor.write(90);: This sends a PWM signal to the drone's motor to start the watering process. The motor runs for 5 seconds before stopping.
• client.publish("agriculture/data", payload.c_str());: This sends the collected data (soil moisture, temperature, and humidity) to the MQTT broker for real-time monitoring.

Applications

• Automated watering of crops based on soil moisture levels.
• Real-time environmental monitoring for optimal growing conditions.
• Remote monitoring and control of farming operations using IoT technology.
• Precision farming through automated drone tasks such as crop spraying and surveillance.

Conclusion

The ESP32-powered Smart Agriculture System with Automated Drone Control provides a scalable solution for precision farming. By integrating environmental sensors and drone control, farmers can automate tasks such as irrigation, monitoring, and spraying. This reduces labor costs, increases crop yield, and enhances overall farm management efficiency.