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Smartwatches, smart cars, smart ranching?

Smartwatches, smart cars, smart ranching?

What you need to know: You may have heard the term "smart" used to describe things like cars (i.e., smart cars like Tesla) or devices like Amazon Alexa, and Siri on the iPhone. Although not new in 2021, these smart products have already impacted industries like consumer goods, vehicle safety, and social media. One sector, however, that has not been made "smart" yet is agriculture, and to an even lesser extent, animal agriculture.

In animal agriculture, tracking and maintaining the health and well-being of our animals is both time and money-intensive. At a feedlot, this looks like pen-riders tasked with checking pens for sick or lame animals each morning. At a ranch, it looks like calving checks throughout the night and day, or estrous checks every few hours during the breeding season. Regardless of what it looks like for your operation, agriculture is a labor-intensive and manual-centric industry. And more manual labor means more money spent.

Although agriculture has looked like this historically, it does not mean this is what agriculture will look like in the future. This future is especially relevant when margins are slimmer, and prices are erratic for those producing agriculture products. This new era of agriculture might be closer than expected, especially when reading a recent review discussing the smart-agriculture that already exists.

Current advancements in animal monitoring like pedometers (Fitbit for cows), LiDAR (a 3-Dimensional camera system), and artificial intelligence allow us to monitor animals around the clock with more accuracy and less labor required. These systems can evaluate the animal's gait, time spent eating versus lying, and changes in disposition, and output actionable information to the manager based on observations.

For example, many papers demonstrated accurate detection of lameness in cattle using 3D camera systems, which could be used to detect hoof infections early and prevent animal loss and treatment costs. Other examples are using AI to evaluate calving-related behaviors, measuring an individual's feed consumption with cameras, or tracking animal feeding and standing behaviors throughout the day.

Although wide-ranging, there is much interest and the potential for these technologies to solve current issues in animal production, like early detection of disease and the opportunity to lower labor requirements for previously manual tasks.  

Important to Note:

  • The technology is still relatively expensive and still in the research phase. The adoption of this technology, although approaching, is not here yet.
  • There are limitations of where these technologies can be applied. For example, most research has been conducted in enclosed/small spaces, whereas pastures would require much more sensor coverage to be useful.

Industry Application: I bring up this paper not because you can implement these findings today but because you may start to watch for changes coming to our industry. The adoption of additional technology into the animal agriculture system will have significant effects on animal welfare and productivity and the break-even of operations.

Read more about it: Intelligent Perception-Based Cattle Lameness Detection and Behaviour Recognition: A Review.