How to Implement AI That Will Manage Your Agricultural Robotics
This 5-step guide explains how to implement AI that will manage your agricultural robotics.
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Somehow, when people think about agriculture, the image of a farmer riding a horse with a plow on a field comes to mind. However, if you take a closer look at this industry now, you won’t believe your eyes.
AI is slowly taking over agriculture. Many companies plan to equip their agricultural enterprises with AI-controlled robotics by 2038. According to the IDTechEx report, over 80 companies plan to introduce autonomous machines, like tractors, small agricultural robots, mobile dairy farm robots, drones, and even robots for harvesting to their enterprises.
For sure, the number of enterprises willing to implement AI will be more than 80 even before 2025. Agricultural enterprises are in a constant need to increase their production, and implementing AI-powered agricultural robotics is the best solution.
But where do you start? What should you do to keep up with this rapidly developing technology?
Here are 5 steps to implement AI that will manage your agricultural robotics.
Step #1: Soil Health
Implementing AI that will manage your agricultural robotics must start from determining how healthy soil is. The condition of the soil that will be used for harvesting is a prerequisite for healthy crops. Moreover, the analysis of the soil condition will allow you to choose necessary organic fertilizers to improve soil permeability.
AI-based solutions provide an insightful analysis of the soil sample and give you actionable results. For instance, Trace Genomics, a California-based company, has developed an AI-based system that does the DNA analysis of the soil samples, using specific tools and robotics. Only a small sample of soil is already enough to provide you with the full DNA analysis and actionable results.
The process of harvesting always begins with field tests and preventing defective crops. The soil DNA analysis provides pathogen screening and a complete set of data on soil health. These tests need to be done regularly, during pre-planting as well as post-harvesting steps. AI-based solutions like the one offered by Trace Genomics are effective enough to determine soil health.
Step #2: Weed and Pest Control
When the harvest is planted, regular weed and pest control is crucial for healthy crops. Threats like deforestation and dehydration of soil can impact the quality of crops, leading to various types of diseases, the consequences of which can cost you millions of dollars.
To prevent this from happening, there are various AI-based solutions that use robotics for screening and preventing disease. For instance, the revolutionary Blue River Technology has created a robot called “See and Spray” that uses computer vision and machine learning.
It detects weakened crops that have been brought down by weeds and sprays them. The perk of this technology is that the robot only sprays effected crops instead of covering the entire field with pesticides.
Step #3: Detecting Disease
What if your crops have been affected by disease? AI-powered apps that enable robotics to detect weakened crops are a perfect solution to that.
One such app called Plantix is a perfect solution for agricultural enterprises. It is aimed at improving profitability by doing a health check of your crops to provide full disease control. The biggest advantage of this app is that it has the complete library on plant diseases, helping you detect the problem and quickly come up with the solution.
Apps like Plantix use machine learning, which is an AI-powered feature that allows robots to operate according to a certain given function. When the robot detects a disease, it archives all the relevant information as well as data on how you can solve and prevent it from occurring. This is a very useful feature for agricultural enterprises.
Step #4: Weather Prediction
Weather affects health and crop performance very much. But it’s not always possible to predict it with the existing standard tools.
Moreover, it’s getting harder and harder to predict the weather for agricultural purposes because of the drastic effects of climate change. “Changes in temperature, as well as the growth of atmospheric carbon dioxide, have a significant effect on weather, and on agriculture consequently,” says Martin Heuter, a researcher at Flatfy.
The AI-based solution for agricultural robotics allows farmers to predict weather and analyze crop sustainability. For instance, aWhere, the system based on the machine learning algorithm, uses the connection to satellites to help you predict the weather. Such AI-powered technology is very effective and precise and will be of great help for agriculture.
Step #5: Harvesting Crops
Lastly, let’s talk about AI-based solutions for harvesting. Harvesting is known to be quite labor-intensive, however, with CROO AI-powered robotics, it doesn’t have to be. This system powers the robots to harvest any types of plants with the help of automation.
The company called Harvest CROO Robotics, established in 2013, offers a robot that can harvest strawberries and pack them. This robot can harvest up to 8 acres a day and replaces around 30 human workers. This AI-powered solution is a great way to maintain high levels of production and to save you considerable amounts of money.
The Bottom Line
Implementing AI that will manage your agricultural robotics is a gradual and time-consuming process, but it will definitely bring you a lot of benefits. Hopefully, this step-by-step guide will help you get started and will introduce your agricultural business to the future.
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