Piglets walking around

Chinese farmers aim to use machine learning to manage their large swine farms. The tech is similar to, if not the same as, tech we’ve previously mentioned here, like the pig belt that saves piglets’ lives, the AI that detects chicken sicknesses, and the cow-identifying computer vision tool. But beyond using sound-triggered shocking belts to keep mommas from crushing their distressed piglets, identifying when animals are vocalizing their sicknesses, and tracking individual animals with computer vision, these swine farms will also assign some sort of health score to each pig by using data on a pig’s individual daily physical activity and temperature readings from infrared sensors.

What are the implications? Farmers, who have too many pigs to realistically keep track of, will have the help of computer vision to count new piglets on a daily basis and identify each pig’s physical activity. Machine learning algorithms will help save the lives of piglets being crushed and indicate the health of each individual pig.

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Farmers have to work hard for their livelihoods, and undoubtedly they welcome advancements that make their lives easier and increase profit margins. Now, specifically cow farmers can benefit from AI and ML. By using computer vision, farmers can identify and track each one of their cows individually, seeing exactly what they ate and how much, as well as when they might be sick.

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This AI tells you when they eat, sleep, drink, walk, rest. It also predicts their sicknesses, their fertility, and their body temperature—these bovine have no privacy. But the company that created this tech says all this data is helping dairy farmers improve milk production by 30 percent, and it’s also helping cows become healthier, and hopefully happier. It tracks cow activities with a neck sensor and then uses the collected data to inform farmers about their cows’ health. All farmers have to do is check the stats on their apps.

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Humans translating wild and domestic animal languages is not a new idea—this researcher, alone in the jungle, realized by deciphering monkey sounds that a leopard was tracking him—but now there’s an AI that can help, at least with chicken linguistics. It successfully translates certain chicken sounds, with near-100-percent accuracy. So far, it can tell you when they’re saying they’re hot or stressed, and bonus, it can detect congestion in their voices, flagging when they’re getting sick. A Chicken Run escape may not work so well these days.

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When you think “John Deere,” you probably don’t think “AI.” But that may need to change because precision farming is becoming a thing, and John Deere is leveraging machine learning and computer vision to do it. These tools can help the industry use less herbicides, which may be a win-win for everyone.

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Like Prospera’s AI application, iUNU’s application wants to help farmers by placing cameras on tracks installed in their greenhouse ceilings. These cameras will use computer vision to identify health problems with growing plants. The only distinction between the two, as far as we can tell, is that iUNU claims its tracks will be able to be used with other devices as well, and their product will be a platform instead of just one solo product.

Photo by Agence Producteurs Locaux Damien Kühn on Unsplash

Imagine 8,000 employees once a week inching plant by plant through massive greenhouses. Their goal is to identify tomato plants that might be infested or dying. Now there’s a system that can help. Tomato farmers set up cameras that zoom back and forth on ceiling tracks continuously taking pictures of the plants. Then from there, artificial intelligence identifies which plants are in distress, saving thousands of man hours.

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With all the illegal activities that perpetually orbit fishing, the last thing fishermen want is to be pegged for keeping contraband catch. But it can be tough to identify what species a fish is, never mind which regulations apply to that species. With this app, however, the life of a fisherman just got easier.

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