Computer vision is cultivating transformative growth across the agricultural space by helping ranchers and farmers generate predictive insights, automate key processes, and more. Cutting-edge solutions are improving crop yields, enabling a higher quality of care for livestock animals, and refining timeworn practices for a new era.
SmoothAg is one enterprise leveraging real-time video analytics to augment the capabilities of the agricultural workforce and drive AI-powered innovation. Their new Ranch Rover not only navigates terrain to autonomously make feed deliveries, but also collects visual data with the help of computer vision.
In a new two-part podcast conversation, I’m joined by SmoothAg CEO, River McTasney, and Head of Corporate Development, Hunter Allemand. Part 1 of the discussion focuses on the expertise Allemand and McTasney bring to SmoothAg, the origins of their business, the impressive capabilities of their autonomous Ranch Rover, and more of the exciting changes enabled by emerging tech like computer vision.
Check it out below.
Bennett Glace: Welcome to AI and Plainsight, the Computer Vision podcast, where we chat with Vision AI pros to discuss the latest use cases and new applications, expanding our understanding of computer vision in production.
I’m Bennett Glace, and today we’re taking a closer look at some of the ways computer vision is transforming ranching, farming, and agribusiness. Autonomous vehicles present arguably the most exciting use case for computer vision. While this technology, once the stuff of science fiction, still has a long way to go before self-driving cars become an everyday sight for commuters and pedestrians, certain self-driving vehicles are already driving enterprises into a new era.
Smooth Ag’s V1 Ranch Rover is one such vehicle. The first of its kind, self-driving rover navigates ranch and farm terrain to make feed deliveries. Equipped with computer vision solutions from Plainsight, it gains impressive data collecting capabilities to support a broad range of potentially game-changing use cases.
Today we’re joined by the founders of Smooth Ag, CEO, River McTasney, and Head of Corporate Development, Hunter Allemand. Thanks for joining us. How’s it going guys?
Hunter Allemand: Hi. Thanks for having us.
River McTasney: Yeah, appreciate it, Bennett. I’m really excited to talk to you.
BG: So, tell us a little bit about yourselves. What did you guys do before Smooth Ag and how did Smooth Ag get started?
RM: I grew up north of Abilene, Texas in a little town called Haskell. We moved out to the ranch about junior high and I lived on our family ranch until I graduated and I went to school at Texas A&M. I got a degree in construction management and that helped bring a business understanding to the problem solving skills I had acquired during my rural upbringing. You’ll see that a lot of rural kids, people that grew up in that setting, have a very multidisciplinary set of problem solving skills. Post-A&M, I didn’t actually go right into the construction industry. I took a sales job, sales-type job at an HVAC install and repair company where I did some residential and light commercial HVAC. I did that for a year and decided I didn’t want to be in College Station anymore. I went home. The plan was just to go home for a few months, work on the ranch, apply for jobs, and figure out where I was gonna go next. About two months in, it just kept gnawing at me. Every time I went to feed, I’d think, “why are we still doing it like this? I know the technology is there.” All the different technologies needed to put this application together to have a robot drive the pickup instead of me was already there. Granted, there are changes you’d need to make to your operations, but bottom line, I know the technology’s there – and nobody was putting it together. So I jumped right in. I picked up the Arduino. I started to teach myself how to code. I went and found the open source, all the other technologies needed to package this thing together and I just went to building. That mixture of problem solving skills and business understanding I had picked up as well as an ability to learn and learn fast helped me dive in. Here we are, almost three years later. I did not find another job in that three-month period, we’re stuck with Smooth Ag. I picked up Hunter along the way and I’ll let him explain how we got here.
HA: It’s crazy. The way River and I met was just on Facebook. That’s all it takes, one share, one video. I grew up around ranches and my family’s been ranching ever since we came to the United States four generations ago. I’ve ridden the feed truck so many times. That’s where I learned every word to every Van Halen song. And I realized that’s not a good use of my time. When I saw the Rover, I just knew that was it. I started my career in oil and gas. Then, I started a consulting firm in late 2019 and found River about a year later. I was hoping he would be a new client. I thought it’d be cool to help take him to the next level. The relationship grew from there. A rancher’s job is about so much more than the cattle. I think that gets forgotten. Ranchers are fixing fences, repairing other assets on the ranch, doing so much more than just feeding cattle. We knew the real problem was putting the tech pieces together. River’s done that and now here we are.
BG: Can you tell me a little more about how the Rover itself came to life and how it changes life for ranchers?
RM: We’ve gone from idea to conceptual model to this version 1 prototype model that we have right now. Iit solves this main problem. That’s the labor and supplemental feeding. Everything else revolves around that because that is probably one of the biggest pain points that we can solve for right now. But as we have built and thought, and this idea has evolved, we’ve realized that there are a lot of other things and a lot of other solutions that can piggy-back off of this central solution. Let’s take a look at the feeding aspect. Because of autonomy, we can schedule feeding so we can have consistency. Without necessarily replacing the person, we can optimize labor and minimize human error. Those are two things and we can create routine in the herd because of them. We are now creating a consistent routine that the herd is following. We’re feeding at the same places, at the same time, every time during the week. So you’re bringing organization to all the animals and humans involved. Then we start to get into those piggy-back solutions, that’s the data collection. Plainsight has been a big part of that, providing the software to manage all these sensors and the rover and eventually the cattle inventory. We’re gonna bring all your hardware out there on the pasture, your visualizations, your management, your books, your everything, all into one place.
HA: To expound on what River was saying, when we first started, this was a stripped-down pickup truck frame. That was it. We just took apart a pickup and made it a rolling platform with no cab or steering wheel. Well, it did have a steering wheel, but no one was supposed to steer it. And that’s how it started. We just took what we were originally using, which is trucks, and we stripped it down. I think the biggest problem is that there’s a whole lot of counting that’s going on out there. You’re counting how many times the feed hopper does a cycle to drop. And then you’re counting cattle and, as you know, counting for humans is pretty difficult at scale. Looking at some of the solutions you guys have provided for companies like JBS, you can see how easily human error can creep up when we’re expected to use our eyes to count and store all that data in our brains. ‘Was that 103 or 102?’ And that’s where it’s grown from. As we started diving in, we realized that there was so much more to unpack, but we really started from the grassroots. And, and as we’ve grown, we’ve realized that there’s so much more value that we can provide utilizing technology like what Plainsight offers. I think that that’s where we’re looking at technology in the future, that’s what it comes down to is solving the simplest problem first.
Stay Tuned for Part 2
Make sure to check back in next week for the conclusion to the conversation and our discussion of Plainsight’s role in evolving agriculture. In the meantime, learn more about the ways computer vision solutions are augmenting the capabilities of ranchers and farmers on our blog.