Latest / Closing Market Report / 2025 ADAO | Your Farm and Autonomous Operations

Transcript

2025 ADAO | Your Farm and Autonomous Operations · Closing Market Report

• 0:00
  Todd Gleason: The following presentation was made by John Reed, the director for the Center of Digital Agriculture at the University of Illinois during the March 4 All Day I Got Look at the Beef House in Covington, Indiana. Reid spent nineteen years at John Deere and has recently returned for his second stint at the U of I.
• 0:21
  John Reid: So thank you so much, and thanks for the kind intro. And, I I I just wanna kinda start out is that, how many people use automatic guidance today on your farming systems? Just raise your hand. Okay. So not oh, keep your hands up.
• 0:37
  How many people were using it fifteen years ago? Okay. Quite a bit fewer. How many people use, farm management information system to manage your machine operations on your farm today? A few.
• 0:53
  Okay. So think about that for this numb for this, presentation because a lot of this, is an evolution of technology and, you know, guidance. I used to when I when I first was working in automatic guidance, I was driving up and down the road, and you don't see very many of the GPS receivers on vehicles. You kinda wonder if the technology that's being developed is actually maturing very quickly. But then you start seeing over time that there is more broader adoption as there's value for this.
• 1:22
  I think the the thing I wanna kinda leave you with on automatic with autonomous vehicles is, many of the examples we're seeing today are extensions of all the things and guidance and, all the other types of technologies, including the farm management information system, and then using those together with some opportunities to, in some situations, to remove the operator from the machine. So just to get started with this, what are we seeing in terms of autonomous vehicles? We've had lots of press release, and we live in an age of social media. So you see CES, for example, John Deere announces their new extension. For several years, they've been talking about this.
• 2:07
  And, last year, they talked about doing one production step, tillage, and, in showing how it could be done autonomously, whereas this year, they're much broader vision. They're talking about how these production steps could be more of them. Okay. So that's heading in the right direction. If we're going to have autonomous agriculture on a farm, it can't just be used for one niche thing, and then all the rest of the time, you don't get utility out of it.
• 2:31
  So that's good. They actually, really interesting with, with John Deere, they're also seeing that this farm management information system, which they call op center, links to other spaces even. So it's used for agriculture today, But if they're going to do autonomy in construction or in golf courses, these other places where there's labor and lots of machinery challenges, then you need to have the same kind of thing. So, what is in an autonomous tractor? First of all, it's a highly automated tractor to begin with.
• 3:01
  It doesn't have to be. Actually, you'll see a lot of companies that, will retrofit a vehicle by putting autonomy kit on existing tractor. But if it's highly automated, it's got more electronic surfaces that can be controlled through software, makes it easier to integrate with, with the autonomous vehicle. Actually, you're talking about the example in Champaign. That was the first Magnum tractor from Case IH that had a CAN bus on it.
• 3:29
  And, for a researcher, it was really a nice way of of doing autonomy because usually I had to give the tractors back every year to the company. I'd spend six months making it into a robot tractor And in three months doing work, well, with, with the changes of having electronics backbone and networks, it became, a one week job of converting, a tractor into an autonomous vehicle. So you've got this highly automated tractor. It's got an ability to sense what's happening in this environment. That's called situational awareness.
• 4:02
  Most commonly, we think about GPS telling where the vehicle is and how you could use that to plant straight or to do operations more efficiently through, through automatic guidance as an example. But it has other situation awareness that's needed too because the most important part of a tractor operating in the field is the operator sitting in the seat and sensing what's going on around the vehicle and, in the implement system as well as, understanding what's happening in the field, where do you wanna go. So it's just it's just not an issue of, that nobody does automatic tractoring or just driving the tractor around the field. You have an implement. You're doing a work task.
• 4:42
  You're trying to get a job done. And, and so there's extra sensors needed. Today, we're starting to see cameras and other types of sensing like that that are looking out ahead of the vehicle to look for people, to sense the roads, to, and then also those cameras are looking around the vehicle and seeing the implement and trying to understand is the implement doing its job. And, and then you as I mentioned, you you see this with some OEMs coming out. Many nearly every OEM is talking about autonomy today and how they're exploring it, getting involved in it.
• 5:15
  You don't see very many price tags for it yet because a lot of this is innovation that is still emerging and, and and it's still evolving. And I think it's almost like a working with individual customers to learn is part of what many companies are doing. However, there are companies that are selling retrofit autonomy. Sabanto is one, out of the Chicago area that'll take any color of vehicle and, basically add an autonomy kit to it, And then they have a management system that helps run those run that vehicle autonomously, and it could be remotely monitored and managed. What's really interesting in this space, though, is, is really not autonomy of the driving, but autonomy of the implement itself.
• 5:59
  And, if you've heard of precision spraying technology like, ExactApply from John Deere or other see and spray types of technologies, These technologies are putting the AI and the intelligence on the implement and, and allowing the implement to work at a level that's beyond what, has been possible in the past, being able to very precisely spray individual weeds and save chemical and get those benefits, but then still have an operator in his seat. And I think this is really kind of an important point about this is that, if we are going to be doing these operations, we need implements that can can be able to sense things that are working and not working that today depend on the operator or the farmer in the seat to detect. So think about a, debris on a on a on a on on a plow shank or or some types of, effects, something breaking. Right now, a lot of the implements are not instrumented to be able to tell that something's wrong. So if you really are gonna have effective autonomy, you don't wanna kinda come back to the field where, a tractor just finished operating and seeing that it hadn't completed its operations.
• 7:11
  So anyhow, this intelligent implement side, is not really autonomy, but it is an element that also has to emerge if, if if autonomous agriculture is going to take place. So, again, we have the tractor. We have guidance systems. We have situational awareness or perception on the vehicle. And then usually, these are tied into, the farm, some kind of farm management information system for autonomy.
• 7:37
  That system is used to essentially understand the fields where you're going to operate, understand, what kind of path plans and and AI is used to generate those plans to cover a field. And, for some operations like tillage, that's that's all you need. You basically can can, designate that. The the operator, the farmer, moves the vehicle to the field, and, and then you can get out and execute the task. I wanna come back to this because that's just, we we're seeing a lot of the visual videos of demonstrating the task working.
• 8:12
  But, when you really think about this, a lot of operations, like your planting or anything that has spring, anything that has materials and inputs that you have to manage, there's a lot of work besides just the execution of the planting or spraying task. You you have to consider, how do you resupply. And, actually, in some in some cases, the some some, there's a there's a robotics company that's looking at automating the material logistics and moving materials to and fro, which seems like also a good idea and be really important for a fully autonomous system. So, so you you have these operations taking place, and I wanna kinda kinda talk about the jobs to be done. People are showing autonomy in terms of, okay.
• 8:59
  I'm going to get out of the tractor, hit go, and, this vehicle is going to perform its tillage operation over a field. And, but some of the big challenges are getting to that point of being able to hit go and running that application. So for example, if you start at your farm site and your field is some distance away, you can't autonomously go on the highways today. It's not possible. And, in fact, I I think it's a really hard challenge.
• 9:28
  I don't expect to to see that, and and it'd be it's even in automotive or seeing that autonomy isn't where, it needs to be. And, actually, in agriculture, I think it's got more potential. But, okay, you have to move the equipment to the field. And, okay, the next and maybe you have materials and things to set up the job that are done. And then, actually, when you're running the job, you're monitoring the task.
• 9:50
  And these are things that the farm management information systems can do. They can essentially load data that understands what operation took place, how accurate was it done. And as as long as you don't have any materials to, supply to the vehicle, like seed to a planter or, or fertilizer, then then, you know, it's probably okay for those types of operations. But if you need to logistically do those things, then somebody needs to be involved or additional autonomy is needed to make those things happen. And then after the job is done, tractor finishes, stops, shuts down, well, somebody has to go fetch it and bring it back and clean up the operation.
• 10:28
  So all the things that you have to do when you're doing the operation, really, we're only talking about one piece of it where the vehicle is driving autonomously and doing these operations. So it's really very, very possible to do it today. The, the benefits of it are still somewhat emerging. And there are places where there are benefits, but I just wanna kinda point out that, you know, there's a this is still kind of the first inning of a long game, and, we're at the very beginning of seeing what's possible. And, like guidance at the very beginning, only a few people, lead adopters, were adopting it.
• 11:06
  You know, I'd expect this as even more challenging because of the accumulation of technologies that are needed to make autonomy happen. And then, and then some of these other operations to get the job done, which is part of the complexity of the of that task. So some good news though are there are probably, there are many cases which could be compelling examples of, of autonomy. One of them, for example, you see with, combine harvesting operations where you have a tractor and a green cart that's moving between the combine and the edge of the field to transport materials. Can that be made autonomous?
• 11:44
  Because you're kind of in an open field. There's kind of a fixed location except for the combine, which is always moving. And, autonomy could be a way of of of helping a single operator be able to harvest, and the logistics management, at least to the edge of the field, can be handled. And that's that's gonna be an example where these accumulation of technologies can come together to provide, that type of opportunity. In spring, chemicals in orchards and I know that probably most of you aren't dealing with specialty crops, but, in those kinds of operations, you may not want to be on the vehicle when you're spraying because some of the some of these chemicals have a long period of time before you can reenter the orchard, so why not get the operator off the machine entirely?
• 12:28
  And, so so where do these, examples, pay off? And I'll give a couple of examples for you. It tends to be on for for many of the applications where there's a lot of already labor involved, and, autonomy is a way of getting better performance output out of labor that could be low skilled and, display some of that. So one example in, there's a there's a study by the Western Growers, about a system called carbon robotics. It's not a it's not a autonomous system, but it's a very intelligent laser weed control system.
• 13:09
  Very expensive. It's about a million dollars just for the implement. But in those operations where you have, three crews of 25 people weeding in the field, this kind of system, has a payback and and can can provide value in that particular scenario. So, again, that's one scenario. Another example, that I worked on in the past was working with Citrus Operations in Florida where they have lots of lots of acreage.
• 13:41
  They're spraying, chemicals or they're mowing, and they have just fleets of machines that are doing this all the time. And, we were able to show that we could take the drivers out of three to five machines and train a new kind of skill level, somebody that was a mission manager that could sit almost like a security guard either in a truck or in a remote, air conditioned office. And, they could monitor these systems working. And and from our data working with these, with these, operators for over eighteen months, they achieved 30% more productivity than people that were driving the machines. And, part of that was because through planning, you you the orchards are somewhat confusing, and, they're not all just perfectly straight rows, so they could avoid passing through places twice.
• 14:32
  That was one improvement in productivity. The other thing was that, a human operator in these machines with trees being close would only drive a certain speed, but it was safer to drive faster with the autonomy system. And it wasn't, you know, more like in the in the cab. You would be nervous, perhaps, driving that speed. But, with autonomy, it was visibly and and and actually performed safely in that way.
• 14:57
  So what's what's coming with, these technologies is that, as I said, I think it's just a long journey. We're seeing a lot of the initial things like we asked in the guidance questions. There are a few early adopters that are trying these technologies, and I think we're going to see moving through the hype as industry gets more experienced. We're gonna see more and more examples of this. It it is not going to be for everyone.
• 15:24
  In fact, I would say if you are interested in autonomy, the really, the the journey is still start with automation and, get the value of the productivity of automatic guidance and some of these other type of things. And, integrating into farm management information systems is kind of a next step, that leads to this. And, you know, as I said, twenty five years ago when I was looking at guidance, actually, similar to to what your answers were here. Fairly small adoption rate that grew over time to higher numbers as these systems matured and the cost came down. Autonomy will be more complex because it's like a a suite of technologies that integrate together.
• 16:10
  And, yes, the technology readiness is there. We're still working on the, viability and understanding the business the business model, and there is some customer value on certain types of applications in terms of, especially around labor productivity and performance. So I'll just stop there and use the time for questions if anyone has any. Yeah. It's it's it's certainly putting sensors in the, ground in the soil would be something that, many many have looked at.
• 16:44
  And so I I don't know that it's commercially available yet, but, you know, I know there is things like a, John Deere has something called exact shot that spraying a little bit of, chemicals on the seed at planting time with their with their high precision, exact emerge. But, yeah, I think that's types of devices that, we use today for connectivity, sensing, and things like that. Can they be integrated into the, into the, ground engaging parts is is certainly a possibility.
• 17:14
  Todd Gleason: So the question was whether or not you could soil test as you were planting or doing something some other operation simultaneously. Other questions about autonomous agriculture that might be on your farm. So I've I've got a series of questions for you. The university, to this point and we started with autonomous act with large tractors, have moved to, smaller vehicles, usually robots. What's the in between or what what what do you see?
• 17:46
  John Reid: Yeah. Actually, I'm, you know, if you're if you work for a large OEM, and I did for twenty years, you kind of see the productivity we get out of these machines of last hundred years, wider, bigger, faster, high performance. Adding autonomy to those machines is, an element of trying to achieve increased productivity, with do more with less, is like what John Deere says. Now on the other end of the spectrum are small robots that are going down between the rows. And, you know, my center, and I came into the center a couple years ago, but they've talked about this a lot.
• 18:23
  And they're showing things like cover cropping. But, you know, think about the energy and and power requirements of agriculture. I think we all go hungry if we just depended on small small robots to, to do some of those types of things. So they do unique things, like if you wanted to plant seed, in August between corn so that you start a cover crop, just before harvest, Definitely doable. Can it connect date collect data?
• 18:48
  Yes. Drones also can collect
• 18:50
  Todd Gleason: collect data faster. Yeah. What what what are your thoughts about drone technology?
• 18:54
  John Reid: Some some of it is, one of my my greatest experiences is for a period of time, I had to work with advanced marketing people and put technology and marketing together. And, every technologist has a hammer. So if you're doing the small robot or you're doing the big robot, you know, you wanna do that, and that's what you know. And, but I think the real reality is you have to understand what's the what's the, effectiveness of the solution? What does it cost?
• 19:19
  What is it what's the how much work does it take to get it done? And, I I think there's just a variety of options that we have today, including remote sensing. I've used remote sensing services that are available today that give me a prediction of yield on a field that are are better than the yield monitor on the combine. So, so, you know, that's that's actually easy. You can pay a subscription fee to give them your farm.
• 19:44
  I mean, you just buy it for your own area of land, and, and you have a layer of information that can help manage to how the combine operates more efficiently. So, you know, again, we have to kind of be a little agnostic to the specific version of technology. Now back to this point, I think there are going to be some operations. So Lymptech is a company that shows a solar powered sprayer. And, they've even I talked about this idea of tendering.
• 20:12
  They even show that they're building a unit that it can park and tender. And this this just runs really slow because it's solar powered, but it runs all the time. And, and so, the idea of being able to do, you know, perhaps some levels of weed management in certain operations and not have to touch it, if you really don't have to touch it, then that's potentially valuable for for the farmer to consider. On the other hand, if you have to spend a lot of time and resources to get everything set up and use it, and then you're going to stand there in the field and watch it while it's operating, well, that doesn't feel like it improved your performance product productivity very much. It just is kind of a novelty that's pretty cool to see.
• 20:52
  So we have to kinda get past those early learning phases to where you can trust have trust in automation, and you don't have to sit there and and and babysit it.
• 21:01
  Todd Gleason: One of your colleagues, when you were still at Deere, was here a couple of years ago talking about and he added up the combine section, was talking about machine learning versus AI. That's in your wheelhouse. Yep. What do you think about the difference between the two, if there is one?
• 21:17
  John Reid: Well, I don't I mean, machine learning is a form of AI. But one of the reasons I'm really enjoying being back at university is, the the power of AI is is is getting cheaper, and it's more capable today, and can do some really interesting things. My team is working on things like, embodied AI that can go inside the machine and and collaborate with the farmer in terms of advice and ask questions, document information. So you don't have to the display, but you can just have information automatically ingested. We actually have a AI tool that's a large language model called CropWizard, and there'll be a big announcement on this this week.
• 21:54
  And, working with a number of, companies where, it's kind of an expert agronomist. It's been trained on USDA data and agronomy. You can all go find it at uiuc.chat, and it's one of the programs that's listed there. It's, also in the early phases of development, but it's based by factual information that, scientists have collected. And it ends up being a quick way of answering questions and getting a perspective.
• 22:22
  Now, when you get the answer, you still have to use your brain. You have to understand, like, everything else. Is it, telling me something that's factually true? Look at the references. But it's kind of a nice aid that could be integrated in the machinery as well as used in the farm, site.
• 22:37
  Todd Gleason: Yeah. So, essentially, you can go to UIUC.Chat. Chat.
• 22:41
  John Reid: C h a t.
• 22:42
  Todd Gleason: Yeah. Do you have to put the EDU on the end? Is it No.
• 22:44
  John Reid: Just uicuiuc.chat.
• 22:48
  Todd Gleason: Yeah. And then it's like it's like chat g p t or any of the others. So you can ask it questions. It's crop wizard. So you can ask it questions about whatever as it's related to crops, and it will go out and find within a defined set of good facts an answer for you.
• 23:07
  John Reid: Yeah.
• 23:08
  Todd Gleason: So try that out. That'd be interesting. Yes. I have a couple of other questions. So on autonomous agriculture, I don't think that your colleague said upfront, but I know.
• 23:20
  He thinks that the platform, the combines itself, can do a better job of setting
• 23:29
  John Reid: the combine. Did you take have Don Pfeiffer here by any chance? No. Just trying to figure out I
• 23:34
  Todd Gleason: honestly, does anybody remember the guy's name? I don't remember his name at the moment. But, no, that one doesn't ring a bell.
• 23:39
  John Reid: Actually, well, this is this is actually my one of my last projects at Deere. We worked on combine automation. Actually, the x nine, has a a a package on it with forward looking perception that sees the crop and gives information about what's coming at the combine. Actually, you know, the thing is this is that, we we documented over 500,000 acres around the world of people harvesting different crops. And we found if you gave them an, a zero to a % score, the best operators were only performing in the 80% range, and that was only for a few hours a day.
• 24:17
  And, actually, it was more common to see that, especially large operations that had lots of unskilled labor, that they're operating in the 50% range. In some some cases, they were setting up the combine for one crop, using it for a different one, not changing it, and the performance was because you weren't getting machine itself. So that's a that's an area where, you don't even have to automatically control it. Combine harvesting changes with the temperatures during the day. It changes with moisture content, weather.
• 24:45
  It changes with topography, uphill, downhill. How many people here, when you're busy harvesting, take somebody in your family and put them in a cab and say, set the settings here and don't touch anything? How many people do that?
• 25:00
  Todd Gleason: Raise your hands.
• 25:03
  John Reid: I mean and so, actually, we had a lot of fleet customers that told us they didn't care about fuel consumption, but with the digital information that's on the on the machines today, once we showed them the significant dollar
• 25:17
  Todd Gleason: Yeah.
• 25:18
  John Reid: That they were spending on harvesting crop and and and losing some of it out the back of the machine or, or burning too much fuel to get that that same type of performance, then it is a real interesting area of optimization. And, frankly, I think it's as it's probably it's a precursor to autonomy. If I can get that kind of performance and really optimize a machine, then, then I'm ready to talk about stepping out of the cab because it doesn't need me so much.
• 25:44
  Todd Gleason: Any other questions? Yes, sir. Oh, I didn't catch that. Can you repeat?
• 25:50
  John Reid: I I is is it actually you're asking about having a service model? Yeah. Yeah. I think it's really interesting because, you know, you think about the machines themselves is that that the machine is a pretty significant investment. And, the autonomy, especially in the early phases, is going to need a lot of hands on or observations by the company, the perception systems.
• 26:11
  Are they working? Is, you know, is it is it the same as it was last year? And so having kind of a model that's similar to, you know, satellite TV. You buy your TV, but you buy the, you buy the satellite service. That kind of subscription model could work.
• 26:29
  I don't see very many of the OEMs or even the small players. Some of them may be going that way. I think there's value in them being able to see how the fleet of machines work as long as they're not, compromising the farmer's data so that they can make those systems better by the learning they get between systems. So in the in the early phases particularly, I think a well, I actually believe in the long run, a services model might be better than thinking about a farmer is going to basically set this up and stand in the field. I'd rather, have a service provider that, you know, train community college students to, understand how to run these systems.
• 27:08
  And they afford they can afford the cost of the assets, and they deploy it by serving lots of farmers in a particular area is, is not a bad