Being able to see technology applied to industries that have a direct impact on the lives of people all over the world is incredibly satisfying for me. A good example is the widespread use of artificial intelligence (AI) in the agricultural industry, which is a great example of this. According to the University of California at Berkeley, the global food and agribusiness industry is worth $5 trillion today and is expected to continue to grow. Agriculture is typically considered to be a sector that is less “digitized” than the rest of the economy, but it is experiencing a resurgence as a result of technological advancements such as artificial intelligence.
The Importance of AI in Agriculture
Both developed and developing countries benefit from agricultural production, which has been made possible by advances in artificial intelligence (AI). Farmers can now produce more output of higher quality with fewer resources thanks to these advancements in AI technologies. According to Science Direct, there are already an estimated 75 million connected devices on farms today, and by 2050, it is expected that the average farm will generate more than 4 million data points every day, on average. AI works by processing data input (which can include anything from weather to soil to insects) and processing it extremely quickly, allowing farmers to make more timely and better farming decisions than they otherwise would. Furthermore, it is capable of learning as it goes along and applying what it has learned to new problems in the future.
There are four major factors driving the expansion of artificial intelligence in agriculture:
- As the world’s population continues to grow, there is an increasing demand for food and crop production.
- Farms are already implementing a variety of information management systems and technologies to improve the efficiency of their farming activities.
- There is a great need to increase crop productivity, and artificial intelligence can accomplish this quickly and efficiently.
- Governments all over the world are encouraging the adoption of modern agricultural techniques, such as artificial intelligence (AI).
Using Agricultural Robotics to Control Weeds in the Field
Weed control is becoming an increasingly important priority for farmers, who are concerned about the threat of herbicide resistance in many species of weeds. The Weed Science Society of America conducted a study that found that uncontrolled weeds in corn and soybean crops alone cause farmers to lose $43 billion in revenue every year.
Today’s artificial intelligence-driven equipment, dubbed “See and Spray,” can reduce herbicide use by 80-90 percent through the use of vision processing and machine learning technology. A weed detection system works by installing cameras that use computer vision and machine learning to make instant decisions on whether or not an individual plant is a weed. As the equipment travels through a field, it processes images at a rate of 20 times per second, comparing them to a library of one million images in real time. Upon detecting the presence of a weed, it determines the appropriate treatment for each plant and only sprays the weeds in question. It is familiar with the various sizes and species, and it is able to reduce human error while also completing weed control in record time.
Next, in our exploration of artificial intelligence in agriculture, let’s take a look at the predictive weather applications.
Applications of Artificial Intelligence in Predictive Weather
Weather monitoring is obviously important for farmers all over the world, and artificial intelligence is now being used to assist farmers in reducing the damage caused by bad weather. The most important weather data that can be analyzed with artificial intelligence are as follows:
Using analytical algorithms, artificial intelligence can quickly analyze historical rainfall patterns over a specified period of time and make predictions about the future.
Artificial intelligence algorithms assist in the addition of analytics to the tracking of changing temperatures over the course of a given day, month, or year, and in providing a better outlook for future planning.
Wind and Air Pressure
The direction and speed of the wind, as well as the pressure of the air, are all important predictors of storms and other adverse weather changes.
A critical metric for preparing for the amount of rain that can be expected and for more intelligently utilizing available water resources.
It is possible to collect and consolidate data points from all of these categories in a single platform, allowing farmers to monitor changes and develop more predictive farming strategies. Even better, they are able to share data with other farmers in order to create forecasts for a larger geographical area. Predictive weather modeling has the potential to prevent up to 90 percent of crop losses, with one quarter of those losses potentially avoidable through better planning.
As we continue our exploration of artificial intelligence in agriculture, let’s look at how it can assist with pest control.
Intelligently Fighting Pests
Drones powered by artificial intelligence are now assisting farmers in the fight against disease and pests. A special drone camera, which is being used in Leones, Argentina, flies low over 150 acres of wheat and is able to inspect the crops stalk by stalk for signs of fungal infection that could jeopardize their production. The robot is powered by computer vision, a type of artificial intelligence that is increasingly being used in these types of surveillance cameras. The AI engine is capable of teaching itself how to identify and tag each potential threat, whether it is an insect, fungus, or other type of danger. Drones serve as the “eyes” of the operation for farmers, while artificial intelligence and machine learning intelligence serve as the “brains.”
Next, let’s look at how using artificial intelligence in agriculture benefits the crops.
Crop and soil health monitoring should be improved.
Soil is critical to the health of crops, and artificial intelligence is quickly becoming a key tool for monitoring farmland soil. Among the innovations is a deep learning app developed by a Berlin-based company that can detect potential defects and nutrient deficiencies in the soil. Foliage patterns are associated with soil defects, as well as the impact of insects and disease on crops, according to software algorithms. When artificial intelligence-driven image recognition detects potential defects, it notifies the farmer, who can then be advised on various soil restoration options.
The Growing Importance of Upskilling in Artificial Intelligence
Artificial intelligence (AI) is providing a real lifeline to farmers and is assisting in the preservation of the global agriculture industry’s strength and health. Courses in machine learning and deep learning can provide you with the foundation you need to start a technology career that will have a significant impact on industries such as agriculture and food processing.