Exploring Smart Agriculture With Iot And Python

Introduction

Welcome to this post where we will delve into the applications of Internet of Things (IoT) in Smart Agriculture using Python. Why Agriculture you ask? Agriculture is the bedrock of human survival and with the global population ever increasing, technologies like IoT are vital in meeting these surge in demand. In this post, we'll develop a small Python application that collects temperature and humidity data from a hypothetical farm sensor.

Smart Agriculture With IoT

Smart Agriculture is a revolutionizing farm trend that allows growers and farmers to reduce waste and increase productivity. From the data collected, whether it is soil moisture levels, weather conditions, or plant growth, farmers can make smarter decisions about the resources, like water, fertilizers and seeds.

We'll Need Python

Python is an excellent choice for this task as it is simple to learn yet powerful enough to handle this kind of operation. With Python having a number of libraries that can handle time series data and data visualisation as well, we can build a beautiful and effective dashboard with real-time data from our IoT devices.

Let's Get Hands-On

In this post, we are going to use a popular Python library called Paho MQTT which is an open-source client implementation of MQTT protocol used for machine-to-machine (M2M) communication in IoT scenario.

Here's a basic Python MQTT subscriber script that pulls information from a specified topic (our sensor data) and prints it out:

# First install the Paho MQTT library
# pip install paho-mqtt

import paho.mqtt.client as mqtt

# callback function when the client receives a CONNACK response from the server.
def on_connect(client, userdata, flags, rc):
    print(f'Connected with result code {str(rc)}')
    # Subscribing in on_connect() means that if we lose the connection and
    # reconnect then subscriptions will be renewed.
    client.subscribe("Farm/Sensor01")

# The callback for when a PUBLISH message is received from the server.
def on_message(client, userdata, msg):
    print(f'{msg.topic} {str(msg.payload)}')

client = mqtt.Client()
client.on_connect = on_connect
client.on_message = on_message

client.connect("mqtt.eclipse.org", 1883, 60)

# Blocking call that processes network traffic, dispatches callbacks and
# handles reconnecting.
# Other loop*() functions are available that give a threaded interface and a
# manual interface.
client.loop_forever()

This script will print out the temperature and humidity data published to the "Farm/Sensor01" topic. This data can be processed further to provide insights that will enable farm owners to increase efficiency and productivity.

Conclusion

IoT in smart agriculture provides opportunities in improving efficiencies in large farms as well as family-owned farms. With Python provides an easy and powerful programming platform, developing and implementing these systems can be done quickly and effectively.