Motorleaf explains how the future of automation lies in advanced artificial intelligence technology. Robots taking over your grow? Often, sophisticated software is all you need.
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Artificial intelligence (AI) is likely a familiar term to many readers, but how this technology can automate tasks and increase efficiencies in your greenhouses may seem unclear. After all, when most people think AI, they think of Skynet from the Terminator series. AI is a lot simpler than you might first think.
What is artificial intelligence?
AI is just sophisticated software, ultimately. And artificial intelligence does not necessarily need to have predetermined logic.
Using artificial intelligence, Motorleaf builds sophisticated software that can actually learn by finding patterns and associations in data -- since data is essentially ‘a lot of information,’ computers are ideal for identifying patterns.
Once the AI software learns the patterns, you can provide the AI new information and ask it, “what do you think will happen under these circumstances?” and the AI tool will offer a prediction and give you its estimated degree of accuracy, which is higher the more training data it has to work with.
An example of computer learning in action.
No need for robots, but just as smart
Machine learning is the type of AI technology we use in our greenhouse automation services. There are no machines involved other than powerful computers -- so no, there’s no robots automating greenhouse tasks in this case. As made apparent by the name “Machine Learning”, our greenhouse technology does learn, and gets more and more accurate as it gets more data sets to work with following each harvest cycle.
For instance, our clients have witnessed a 50% to 70% reduction in error in harvest forecasts from the start; following a year of further learning, the AI technology can reduce errors by more than 70%. The AI technology will also become more accurate in predicting harvest yields weeks into the future.
AI tools for greenhouses get better and better over time. That’s a smart investment if you want your money to go the extra mile.
Why does AI solve problems with harvest forecasts for greenhouses?
There are many factors that influence plant growth and the ripening of produce in your greenhouse. It is impossible for humans to analyze all of these individual factors and know exactly how your plants will grow.
But nothing’s stopping a computer from examining all of these factors at once. AI is able to simultaneously analyze all of these growth factors, providing highly accurate assessments of plant growth. This is why AI works so well for making estimates of future harvests.
AI is better at estimating harvest yields than expert agronomists, which allows you to automate this task so that your Head Growers and agronomists can focus their time on other important issues that a computer may not be able to solve. On average, agronomists free up over a day of time they otherwise spent doing harvest forecasts. Best of all, our technology requires no radical changes to your business.
Editor’s Note : There’s another hidden advantage to machine learning. Machine’s don’t rely on intuition at all, just looking at what works and what doesn’t. Sometimes computers will notice correlations between sets of data that humans would otherwise miss.
Join the agriculture technology revolution and benefit from the latest means to automate your greenhouse. Submit an order or request more information today on our website .
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Motorleaf is poised to disrupt the agricultural industry by using its Agronomist.ai software platform to monitor and predict environments through sensor data. Delivering actionable, data-driven insights to greenhouse operators and indoor farmers is our M.O. Using machine learning and artificial intelligence for yield predictions improvements and optimization, we are committed to helping greenhouse operators match their supply with demand dynamics to help them optimize their marketing dollars, plan their labour needs, and increase their margins. We connect growers to their plants, and to each other.