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January 13, 2021

A Virtual Ride Along with John Deere at CES

Alex Woodie

CES is virtual this year, thanks to the novel coronavirus that doesn’t feel so novel anymore. But that didn’t stop John Deere from showing off its latest farming implements, which are trending heavily towards mass data collection and analysis.

John Deere invited Datanami to participate in a virtual ride along atop one of the massive green machines that farmers use with row crops. Equipped with an Oculus Quest 2 virtual reality goggles, this reporter virtually stepped into the cab of an 8RX 370 Four-Track tractor, while Lane Arthur, John Deere’s vice president of data applications and analytics, provided commentary and navigation support.

For an occupation that’s so down to earth, farming with John Deere’s data-intensive setup is remarkably cloud-like. Once a tractor is in the field, it can drive itself up and down the rows, and perform other actions autonomously, while a 4G cell phone radio continually beams data up to John Deere’s cloud at rates approaching 100 megabits per second.

A farmer doesn’t even have to be in the tractor to know what’s going on. He can check the status of the day’s work–whether it’s plowing, planting, feeding, or harvesting–from the comfort of the Operation Center app running on his smart phone.

On this particular day, John Deere’s Oculus 2 VR goggles were set up to simulate seed planting, which in the American Midwest must occur within a hectic 10-day (non-contiguous period) in mid-spring. The tractor tows a planter attachment that is equipped with up to 48 planter stations, which can automatically plant corn, soybean, or cotton seeds at the proper depth, at rates of up to 100 seeds per second.

Lane Arthur, John Deere’s vice president of data applications and analytics (left) remotely guides your friendly Datanami managing editor through a virtual tractor ride-along during CES

Speed and accuracy during the planting process are the twin traits that will help the farmer maximize his resources. John Deere’s latest planter can run at 10 mph, which is twice the speed of its previous generation planter. As each seed is planted, a sensor on the brush belt detects how deep that seed was planted and how close it is to other seeds. The planting data is aggregated and bubbled up into a dashboard (accessible in the cab and through the Operations Center app) with green, yellow, and red signals to indicate how well things are going.

The Oculus 2 app lets this reporter take the wheel of the tractor, which would not be advisable in a crowded Las Vegas convention hall but is (relatively) safe in the virtual world. Keeping the wheels (or tracks) lined up between the rows is not easy. The soft soil, combined with the heavy planter, makes for a mushy, boat-like ride. But with the GPS-enabled auto-pilot engaged, the tractor can keep itself within an inch of the designated course.

“When it comes to driving that tractor, you can see how you have lots of other thing you need to be watching in the cab, rather than worrying about driving it,” Arthur says. “If I was in an autonomous car, I’d be busy with the radio and the AC. But if you’re in a tractor, you’ve got to worry about how well that planter is working, is the seed guy going to be close to refill the planter. There’s other things you’ve got to focus on.”

The cab of a modern tractor is a data-rich environment (image courtesy John Deere)

All the data collection also lets the farm owner keep tabs on the state of the planting operation, which is time-critical. “In some cases, the owner of the farm may not be driving in that tractor, but may want to know how well is this field being planted. Is he almost done with the field?” Arthur says. “He’s looking at those kinds of things because there’s a lot of logistics involve in getting everything planted in 10 days.”

But the data collection doesn’t end when the seeds are in the ground. John Deere has similar sensors on its sprayer and harvesting attachments that can automatically determine the rate of chemical applications as well as the yield of the harvest. All this data is automatically collected and uploaded into the John Deere cloud to enable farmers to analyze their work and dial in their operations to maximize profit the following season.

“At some point, you finish a year and you look at your fields and ask yourself, did I do the best job possible with that field?” Arthur says. “If you’ve been planting for 40 years, that means you’ve had 40 chances at that field to get it right. So it’s important to use that data to help you.”

From Operations Center, the farmer can pull up heatmaps that show what areas of the field offered the highest yield and which areas were relatively meager. By joining data from the seed planting, the chemical application, and the harvest, John Deere can help farmers determine what changes might be in order for the next season.

John Deere’s Operations Center app uses heatmaps to communicate information about their fields (image courtesy John Deere)

In addition to making changes on a field-by-field basis, the John Deere software can recommend changes on a much smaller scale. The planters and the sprayers can also automatically adjust seed distribution and chemical applications to account for in-field variations, including different soil types, and even adjust to existing waterways.

“Not all the soil in that field is uniform,” Arthur says. “There’s some soil that might be really sand and it didn’t yield very well. Maybe you don’t want to put as much money into that part of the field, so you can program your planter to not plant as much seed there. You can program your sprayer not to spray there.”

The collection and analysis of data is critical to achieve this level of precision with farming. Not all of John Deere’s customers are using data in this way, but the numbers are growing.

“What we’re finding is farmers want to use the data and the analytics to augment their gut. ‘Tell me if I’m right, tell me if I’m wrong, tell me where I need to double down,’” Arthur says. “Let’s use the data to help me make this decision. We’re seeing this more and more.”

Related Items:

Farm Net Seeks to Plant Seeds of Big Data

Farmers Plant for Hyper-Local Forecasts with IBM’s ‘Deep Thunder’

Digital Agriculture Program Yields Promising Prospects

 

 

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