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IoT Agriculture Use Cases & Apps To Plant Seeds For Your Ideas

We help companies enable their IoT ideas—and as a result, we’re constantly hearing about new solutions for business challenges with machine-to-machine (M2M) communication. And some of the most compelling IoT architectures and applications are coming from the agricultural industry.

IoT in agriculture has become one of the fastest growing fields (pun intended) in the M2M space. Today, more than ever before, farmers, ranchers, and conservationists need a method to more effectively utilize and conserve resources. The most effective way to do this is through actionable data, and utilizing M2M communication makes the ongoing collection of that data simple and affordable.

Below, we’ve outlined three generic agricultural use cases and seven IoT agriculture applications that are making it possible for farmers and ranchers to gather the meaningful data they’ve been missing out on.

IoT Agriculture Use Cases

If you asked someone in agriculture 100 years ago how the industry would change in the century to come, they’d probably focus more on climate conditions or water usage than on machines and sensors gathering and transmitting actionable data.

Looking for an overview of IoT agriculture, and how to implement the technology you need?

But today, a farmer, rancher, or conservationist with access to the right IoT architectures can produce greater savings and better yields. Take a look at these use cases—these are solutions we’ve either helped create or integrated for Link Labs customers.

Livestock Monitoring

Livestock monitoring is all about animal husbandry and cost savings. Ranchers are able to use wireless IoT applications to gather data regarding the health, well-being, and location of their cattle. This information saves them money in two ways:

  1. This data helps identify sick animals so they can be pulled from the herd, thus preventing a larger number of sick cattle.
  2. Ranchers who know where their cattle are located can lower labor costs.

There are some specific challenges when instrumenting livestock with sensors. Specifically, it’s quite difficult to outfit cattle with a collar. An alternate option is to use a wireless retrofitted bolus in the cow’s stomach, which can communicate via Bluetooth to an eartag.

Another potential challenge ranchers face is selecting a wireless monitoring technology with enough battery life to last the lifespan of the animal. A beef cow, for example, lives 15 months or longer—Symphony Link can easily connect for that length of time without much infrastructure around the ranch to connect all of the devices.

Conservation Monitoring

While it doesn’t strictly fall under the heading of “agriculture,” monitoring for endangered rhinos is one of the most interesting animal IoT use cases out there. Knowing where rhinos in large game facilities are located can help conservationists protect them and keep poachers from killing the rhinos for their horn.

As one may imagine, collaring a rhino isn’t easy—and we’ve found it isn’t often successful. The collars get ripped off from fighting, and they’ve been known to cause behavioral changes in the rhinos. To solve for this, we are currently examining the idea of a putting Symphony Link devices inside a rhinoceros’s horn.

Plant & Soil Monitoring

Monitoring plant and soil conditions is a simple use case—but it can lead to a fantastic return on investment for farmers utilizing sensing technology. We’ve seen three great general uses for agriculture IoT in this space:

  1. Sensing for soil moisture and nutrients.
  2. Controlling water usage for optimal plant growth.
  3. Determining custom fertilizer profiles based on soil chemistry.

Because the sensors in the use cases above are close to the ground, using a mesh network can be difficult. There simply isn’t enough link budget. But star topologies like Symphony Link are an ideal fit, because one access point can talk to a number of sensors 20-100 square kilometers away.

7 IoT Agriculture & M2M Applications

1. OpenIOT’s Phenonet Project

With the Phenonet Project, plant breeders can evaluate the performance of different wheat varieties using measurements taken from remote sensors. These sensors monitor things like soil temperature, humidity, and air temperature and are often used for crop variety trials. This allows farmers to forecast harvest time, improve plant health, plan irrigation time, and determine frost and heat events. By combining these measurements, plant scientists are able to look at the effects of microclimate and genome, improving the accuracy and speed of plant breeding, which leads to better food quality and increased production.

2. TempuTech’s Wireless Sensor Monitoring

TempuTech wanted to bring better safety to their systems for agricultural storage. Silos and grain elevators can be dangerous places with conveyor belts that can catch fire and dust buildup that can be explosive, so using sensors to track hazards is of massive value. By using GE’s Equipment Insight, TempuTech created a way to connect all of these wireless sensors and help farmers make sense of the data. Using Equipment Insight’s platform, manufacturers can establish baseline performance norms and then set alert and alarm conditions related to temperature, vibration, humidity, and other conditions.

3. CLAAS’s Equipment

CLAAS is one of the world’s leading manufacturers of agricultural engineering equipment. Farmers can operate CLAAS equipment on autopilot, receive advice on how to improve crop flow and minimize grain losses, or automatically optimize equipment performance. The company is partnering with 365FarmNet, a program that enables farmers to manage their entire agricultural holding on a computer or mobile device. It collects data and makes meaningful use of it through field mapping, fertilization planning, nutrient balance, and calendar and planning programs.

4. CleanGrow’s Carbon Nanotube Probe

CleanGrow, based in Ireland, has developed a carbon, nanotube-based sensor for monitoring the level of nutrients in crops, which can allow farmers to alter the color or maturity rate of produce. Conventional nutrient probes are analog devices that capture a composite picture of the current environmental conditions. In CleanGrow’s device, a nanotube sensor tuned to a specific ion—nitrate, sodium, etc.—sits on one side of a membrane. As water passes through the membrane, the sensor detects the presence and quantity of the target ion. Up to 18 different sensors tuned to different ions can be placed on a probe head.

5. PrecisionHawk’s UAV Sensor Platform

PrecisionHawk has created an autonomous UAV that collects high-quality data through a series of sensors that perform civil applications such as surveying, mapping, and imaging of agricultural land. It’s basically a small airplane that performs in-flight observations and monitoring. Before tossing the plane into the air, farmers tell it what field to survey and choose a ground resolution or altitude. Each plane can detect weather conditions in the air using artificial intelligence, so it chooses the best flight path to take based on things like wind speed or air pressure. During the flight, the plane will collect visual, thermal, and multispectral imagery at resolutions up to one centimeter per pixel. When it’s finished, the plane will land in the same place it took off and will have useable data. (Now that’s a cool and useful Internet of Things farming tool!)

6. Precision Planting’s Corn Maze

Radar Family Farms began as a pumpkin farm in the ‘90s, and today offers a 10-acre corn maze to fall visitors. It draws about 50,000 visitors in the midwest each year. The family had previously created the maze by planting all 10 acres of corn and then hiring a company to mow out the shape of the maze. This was a waste in seed—a cost that added up quickly. By using Precision Planting technology, they were able to plant in the shape of the map—a feat they believe is theirs alone in the U.S. today.

7. TeamDev’s Libelium Network For Tobacco Crop Quality

Tobacco is a critical industry in Italy and requires certain environmental and climatic requirements for optimal growth and increased crops. In response to this issue, an Italian software company—TeamDev—deployed Libelium’s Waspmote Plug & Sense platform to collect data on weather conditions that may affect tobacco crops. This technique can be used by tobacco farmers to optimize their crops in conditions not typically suitable for tobacco growth.

In Summary

If you have ideas for how M2M communication could improve your agricultural output (or other outputs, too), let’s talk. We’ve done all the hard work building the hardware and software to power your wireless M2M communication needs.

Want to learn more about how IoT in agriculture is changing the game? Download the free industry overview below.
Agriculture IoT Overview

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