Five IoT Smart Agriculture Use Cases

Traditionally, the agricultural industry has been manually intense and largely reactive. Recent technical advances, such as IoT, have empowered farmers to dramatically change their modus operandi. With IoT, farmers can add intelligence to analog and mechanical devices, streamline processes, gain efficiency, and overall, build stronger businesses. Smart farming is the term for this new approach in agriculture, and there are many examples in the industry.

"With IoT, farmers can add intelligence to analog and mechanical devices, streamline processes, gain efficiency, and overall, build stronger businesses."

-Wittra

Collecting information, such as environmental conditions, improves the quality and quantity of the produce while minimizing risk and waste. The technology can also be adapted to specific machinery and systems, e.g., tractors and sprinkler systems, and use the data collected to provide a complete real-time view of operations. Smart farming impacts every aspect of the agriculture process. The tools track inventory as it makes its way to the farmer, soil conditions as they prepare for planting, crop growth, weather conditions, harvesting, and distribution. As a consequence, smart farming solutions have attracted growing interest, and purchases are on the rise. The global smart agriculture market reached $14.1 billion in 2021 and is expected to increase to $25.25 billion in 2027, exhibiting a CAGR of 9.8 percent. Here are five examples of how smart agriculture is changing farming.

Smart Agriculture Examples

#1: Soil Management

In the agricultural industry, soil can be seen as the very foundation of everything. Growing and harvesting crops constantly fluctuate and can therefore greatly impact a business. With IoT, farmers can do all of the following:

• Gain insight into soil composition, precipitation, and temperature to maximize soil performance.
• Decide if pesticides or fertilizers need to be added or removed.
• Rely on irrigation sensors that can monitor the dryness of the soil and operate sprinklers accordingly.

Agricultural businesses gain real-time visibility into soil viability and unique ground conditions, in order to best utilize the land. IoT offers farmers the means to gain more information about what is happening so they can manage proactively and not reactively.

#2: Crop Monitoring

Farmers want to achieve consistent crop quality and avoid various aberrations, and IoT can help.  Sensors constantly monitor items, such as leaf quality, color, and, root strength; then compare current measurements with historical data, and determine how well crops are growing. With it, farmers can do all of the following:

• Better forecast the production runs.
• See crop growth.
• Note any anomalies, such as diseases, pest infestations, or harsh climate that will lower the yield.
• Understand what their final output will be.
• Set better expectations.
• Enhance product distribution.
• Monitor business expenses more accurately.
• Know when to schedule the next shipment of seeds and grains.

In essence, the business flows more consistently. Once the finished product is out for distribution, the next batch is ready to be planted. The insights lower production risks and empower farmers, so they do not face product shortages and income disruptions.

#3: Predictive Maintenance

Another critical smart agriculture example is predictive maintenance. The advent of intelligent IoT sensors enables suppliers to collect device performance information as their equipment functions. Artificial intelligence, machine learning, and data analytics gauge an asset’s typical efficiency and wear and tear based on items like vibration analysis, oil analysis, and thermal imaging. Predictive models feature algorithms that identify when an asset will need to be maintained, or repaired. The benefits include:

• Lengthened machinery lifecycles.
• Lowered downtime.
• Increased employee productivity.

Data from the U.S. Department of Energy indicates that predictive maintenance is extremely cost-effective. Putting a predictive maintenance program in place yields:

• Tenfold increase in ROI
• 25-30 percent reduction in maintenance costs
• 70-75 percent decrease in breakdowns.
• 35-45 percent reduction in downtime.

In essence, farmers gain a much better way of ensuring that their equipment functions at peak performance.

#4: Livestock Management

Traditional methods of livestock monitoring relied on individuals manually inspecting animals and looking for signs of disease or injury, a costly, highly unreliable, and inefficient method. IoT livestock management solutions take the guesswork out of determining an animal’s health. How does IoT livestock management work? Using a wearable collar or tag, battery-powered sensors monitor an animal’s location, temperature, blood pressure, and heart rate.

The information is wirelessly sent to an application in near-real-time. Farmers access information via mobile devices and so they can do the following:

• Check the health and location of each animal in their herds from anywhere.
• Receive alerts if a metric falls outside of the normal range.
• Know immediately which livestock is affected and which is not.

Also, farmers no longer need to physically examine each animal’s vitals to see if an illness has spread. Temperature tracking helps to determine the peak of mating season. Livestock monitoring solutions also use tracking to gather and store historical data on preferred grazing spots. Keeping livestock healthy is important because if they become ill, their development falls behind their cohorts. Such animals typically do not catch up to the rest of the herd, and they become less valuable to the farmer. With this smart agriculture example, farmers gain more insight into their animals’ health and well-being.

#5: Process Automation

Farmers need to increase efficiency. Decades ago, farmers began replacing manual work with machines. Now, IoT offers them the next step in that process:

• Computer technology to take on work typically done by hired hands.
• Streamline repetitive manual tasks, such as irrigation, fertilization, pest control, and even seed planting.
• Sift through large volumes of performance data, like crop growth, herd eating, and soil conditions.
• Find aberrations.
• Send alerts automatically to staff smartphones, as needed.

Famers become more informed and more proactive with these capabilities. They see problems, dig into the issue, troubleshoot, create workarounds, and work faster and more efficiently.

A Competitive Industry

Farming is a mature, highly competitive, manually intensive industry. The above smart agriculture examples highlight this. Emerging IoT technology streamlines operations in areas like soil management, predictive maintenance, and automation. Using smart sensors to collect environmental and machine metrics enables farmers to make informed decisions and improve just about every aspect of their daily workflow.