How artificial intelligence is transforming agriculture

Agriculture is one of the oldest professions in the world. It is the primary source of a very significant part of our food supply. Farmers grow crops ranging from cotton to corn, supplying the world with many things it needs. Conversely, AI is a very recent human invention. Yet it has many applications in improving the efficiency of several industries and professions. Agriculture is one of them. 

What is Artificial Intelligence?

In the 1950s, pioneers defined artificial intelligence as a machine that could accomplish tasks that would require a human to exert intelligence. This might seem like an overly broad definition to you, and you may be right. If I use intelligence to look for Cox internet prices, does that make Google and Bing AI? The internet is full of AI debate forums arguing over whether the term artificial intelligence is an exaggeration when it comes to many technologies.

However, a typical AI system will demonstrate some or all of the behaviors listed below:

  • Planning
  • Reasoning
  • Learning
  • Perception
  • Motion
  • Problem Solving
  • Manipulation

Many newer AI also have a certain degree of creativity and social intelligence. However, AI like the famous SkyNet from Terminator is still decades away, if at all. Since AI is still fairly new, we are learning about its capabilities, potential, and limitations as we go along. It is present in so many aspects of our daily lives that we don’t even give it a second thought. Google ads, Amazon product suggestions, Siri, Alexa, Google Photos, and many other technologies we use every day are AI.

What is Machine Learning?

Machine learning or ML is a form of analyzing data in a way that allows machines to create analytical models without explicit instructions. Does that sound like a lot to digest? Essentially machine learning is how computers process data to solve problems without any specific instructions.

ML is a branch of AI that has received a lot of attention over recent years. Businesses, in particular, have made efforts to harness the power of ML in analyzing and interpreting data, identifying trends, and automating decision.

Many popular examples of machine learning include:

  • Google’s self-driving car
  • Fraud detection software and alerts
  • Social “listening” tools
  • Online recommendations

AI in Agriculture – Growing Transformation

Agriculture makes up around 6.4% of the global economic production, according to this 2017 GDP sector analysis. Most developing nations rely heavily on agriculture as a means to generate revenue. Agriculture traditionally involved unskilled labor using basic mechanization like tractors and harvesters. However, over recent years, this has changed.

Artificial Intelligence and machine learning have brought about the next phase of the digital revolution. This technology allows the AI in a computer or smart device to “learn” from its environment. AI and ML have had many success stories in many fields. These include financial management, manufacturing, data management, advertising, and much more. However, the leading area is Agriculture. 

Machine learning and Artificial intelligence are leading the charge for a new Agricultural Revolution, especially in the two most significant areas discussed below.

AI in Farm Data Analysis

You might not know this, but farming involves tens of thousands of data points every single day. For one person or even a team, collecting, analyzing, and correctly interpreting this data used to be impossible. But thanks to AI and ML, farmers can now use data-driven techniques to optimize their agricultural output.

We live in an increasingly precise world, even in agriculture. AI and ML can help detect crop diseases, pests, malnutrition, and even predict the weather. AI can detect and target weeds using precision herbicides without toxifying the soil.

Ground data is not the only data farmers can collect and analyze using AI. Thanks to drones, farmers can use algorithms to process visual data from an aerial viewpoint. This can help identify any problem points on the ground, allowing for speedy correction.

AI in Agricultural Workforce Management

Each year sees fewer people entering the agricultural sector. This means there is a growing workforce shortage threatening agricultural production. Most people have shifted from an agrarian society to urban life. My own father was one of the hundreds who came from rural Virginia to Atlanta for comforts like fast food and Cox deals. One way to counter this growing shortage is to use AI bots.

Bots can work in various capacities to augment human efforts. They have uses in automating harvesting, and they do it much more efficiently. They can find and remove weeds more accurately than humans. Most importantly, they can work around the clock without needing wages.

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