Smart Farming: Definition, Importance, Examples [2022 Update]

Smart farming is applying information technology for managing farms.

This approach gives farmers tools and strategies to improve yields and sustainability of agricultural production. The heart of the innovation: smart agricultural technology, which is making its way from other industries (autonomous driving included). 

In this post:

• Smart farming definition
• Reasons why smart farms are important
• Popular uses of smart farming technologies

What is Smart Farming?

Smart farming refers to the use of information and data management technologies in agriculture. These technologies, including software, sensors, and robotics, increase productivity and efficiency of agricultural systems.

Smart farming combines these components:

• Sensors
• IoT (Internet of Things) devices
• Data analytics
• Autonomous robots and drones
• Software applications

Why is Smart Farming Important for Agriculture?

About 15% of farmers (200,000+ farms) are using smart farming technologies at the moment. That’s not a lot, but smart agriculture will become more important than ever before in just several decades.

Here’s why.

We need smart farming to:

• Improve crop health. Optical smart farming technologies allow farmers to identify crop diseases and other problems earlier.
• Reduce the ecological footprint of farming. Precision agriculture systems can reduce the use of harmful chemicals and carbon emissions.
• Help feed the increasing global population. The UN data suggests that the world’s population will grow from 7.7 billion in 2020 to 9.7 billion in 2050.
• Provide food security in climate change scenarios. More efficient smart farming helps to adapt to changing climates while maintaining production levels.
• Achieve higher yields while reducing operating costs. Smart farms achieve higher yields (by 1.75%), lower water use (by 8%), and lower energy costs ($17 to $23 per hectare).

So, the greater use of intelligent farm technologies is crucial not only to improve financial performance. It’s also needed to meet the needs of the growing population.

But—

How exactly will smart farming technology push agriculture to the next level?

Our review of scholarly papers and case studies found many ways in which smart farming is already helping agricultural businesses to grow.

Let’s take a look at the five most interesting ones.

Top Uses of Smart Farming in Agriculture

Farmers have already begun using various smart farming technologies, and their experience has been extraordinary. But these five use cases stand out for their results.

1. Livestock Management and Monitoring

Also called Precision Livestock Farming (PLF), this technology uses IoT devices and predictive analytics software to track aspects of livestock.

These aspects include:

• Behavior
• Feeding patterns
• Health and well-being

How exactly does PLF work?

Let me share an example—

Suppose we manage a large farm with hundreds of cows. We’d like to monitor their health, optimize feeding patterns, and conduct real-time monitoring. The smart farming equipment for this project would have cameras, sensors, and an app.

This equipment can identify:

• Lameness
• Aggression
• Abnormal postures
• Prolonged inactivity
• Unusually shorter feeding sessions
• Shorter step frequency and step length 
• Changes in tail positions (signs of tail biting)

These aspects can be signs of disease, well-being risks, and aggressive behavior. The software can give farmers real-time health status even for individual animals, from as small as chickens to as large as cows.

For example—

By analyzing the motion curve generated by the leg swing of an individual cow (as shown below), an automatic smart farming software gives alerts about lameness.

AI-enabled computer recognition is the smart farming technology that makes livestock management and monitoring possible. Research suggests that farmers can even recognize facial expressions in sheep, giving an early warning of diseases such as mastitis and foot rot.

All these technologies give farmers a real-time monitoring ability, which is critical in the industry, where health status has a major economic impact.

2. Smart Crop Management

Traditionally, farmers have gone to the fields to check on the health of their crops. But imagine you have to inspect your field for hours every day—for large agricultural businesses, this method is simply impractical.

Enter smart farming.

IoT sensors and drones have proven the most valuable for farmers. So, let’s take a closer look at their contribution to crop management.

First, sensors.

Installed on fields, these devices can provide on:

• Moisture levels
• Pesticide levels
• Ambient temperature levels
• Soil properties (organic matter, clay, etc.)
• Presence of CO₂, O₂, and other gases + pH levels

Sensors come in different types (weather stations, optical, electrochemical, etc.) and can provide both real-time and historical data on crop health.

The Electrochemical Society beautifully visualized the whole range of data that smart farming sensors provide, along with the benefits. 

The second device category, drones.

Farm drones can:

• Inspect soil health
• Assess irrigation needs
• Define crop health and maturity
• Detect crop damage caused by pests
• Conduct aerial treatment for crop diseases, weeds, and pests

The technology that makes these operations possible is AI-powered software. Agricultural applications use GPS, image recognition, and various IoT devices to guide drones and let them perform their functions.

Here’s an agricultural drone with an onboard camera equipped with AI software.

So, how exactly can this smart farming technology help?

Let’s consider two use cases: pest detection and spraying.

A sensing drone found unusual forms of plant leaves, suggesting potential pest damage. The image recognition technology ran comparisons with preloaded pictures of healthy leaves and detected abnormalities.

Farmers review the evidence and deploy an actuation drone to distribute the pesticide. The device has an onboard fertilizer tank, so it can spray the affected area with great precision.

This way, farmers can detect potential problems earlier and prevent them. By monitoring fields continuously, they can maximize yields and minimize losses.

Want to learn more about AI and drones in agriculture?

We have another great post for you: AI in Agriculture: Examples, Benefits, Challenges [Latest Data]

3. Greenhouse Monitoring System

A greenhouse monitoring system, aka “smart greenhouse,” is a greenhouse equipped with sensors controlling environmental conditions automatically. 

The essential components of the system include:

• Sensors
• Wireless connectivity (infrastructure + cloud)
• User software (a desktop and/or a mobile app)

Here’s how these three components combine to generate data on conditions. 

Thanks to this system, a smart greenhouse:

• Maintains an ideal micro climate. Temperature, humidity, light, and other IoT sensors control environmental conditions.
• Manages fertilization and irrigation. Sensors collecting soil health data provide data based on which farmers can activate sprinkler and irrigation systems.
• Provides data on potential plant diseases. Continuous environmental readings can help farmers recognize diseases and pest damage and take action early.

This smart farming technology removes the need for farmers to control environmental conditions manually. The data received by the software can be easily viewed and analyzed, providing unprecedented insights into the health of plants.

More agricultural businesses start using this smart farming technology to generate higher yields while reducing overall operating costs.

In fact—

The global smart warehouse market size reached $1.54 billion in 2020. The forecast suggests that the market is expected to grow by almost 10% annually. 

Manufacturing is another major field where IoT is actively used to increase the productivity and efficiency of operations. 

Learn more: Five Uses of IoT Apps in Manufacturing

4. Autonomous Ground Vehicles

Drones aren’t the only robots involved in smart farming. Autonomous driving technology has also arrived in tractors and other agricultural machinery. It’s made autonomous farming possible and reduced the need for human labor.

The technology itself is fairly simple—

AI and location tracking software containing map data programs the vehicle’s position and controls speed. So, it’s just about GPS and controlling equipment counted on the machinery (cameras and sensors)

Simple as that.

That’s why self-driving tractors in particular are becoming a norm—the U.S. alone has over 10,000 unique and retrofitted units. Here’s how one of them looks like.

Here’s what autonomous vehicles mean for farms:

• Elimination of human errors
• Increased fieldwork accuracy
• Reduced need for human labor
• Optimized production schedules
• Doing repetitive work (digging, spraying, harvesting)

The ultimate goal of this smart farming technology: enable super precise farming while alleviating farmers from having to be involved in field activities.

AI is everywhere in smart farming. But the technology is also helping businesses in many other industries.

Here are some reads if you’re interested:

• Use Cases of AI in Finance
• Machine Learning for Trading
• Healthcare and AI: the Impact
• How AI is Transforming the Automotive Industry
• How Machine Learning Enhances Supply Chains

5. Smart Farm Management Software

Smart farming software is designed to help with various aspects of farm management. Basically, it’s a hub with historical and real-time data and information about the facility, which farmers use to plan, monitor, and analyze activities.

The software might contain:

• Weather records
• Animal monitoring data
• Farming equipment condition status
• Ideal and historical planting schedule
• Real-time environmental conditions for field monitoring
• Record management (revenues, orders, expenditures, etc.)
• Predictive analytics (yield size, expected waste, profitability, etc.)

Together, this information allows farmers to manage everything using one app. Besides farm management, they can also manage finances and human resources.

Often, this smart farming tool is built as custom software solutions for specific farms to include only the most useful options.

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Want to Learn More About Smart Farming?

If you’re interested in knowing more about the impact of smart farming, these credible, peer-reviewed resources should be useful.

• Precision Agriculture Journal [Open access]. Research on emerging intelligent farming technologies and their application
• Smart Agricultural Technology Journal [Open access]. Contains the latest case studies and research on practical applications of smart farming.
• ​​Electrochemical Sensors for Soil Quality Assessment [Open access]. A scholarly article discussing state-of-the-art electrochemical sensing technology developed to monitor soil quality for agricultural businesses.
• Cost analysis of autonomous battery electric field tractors in agriculture. [Open access]. An article proving the cost-efficiency of autonomous tractors.