Though the benefits of combining data with artificial intelligence technologies might seem obvious, its applications are less so. While industries like finance or marketing generate tons of data and are natural fits for artificial intelligence programs, a bit of innovation and necessity are required before artificial intelligence and big data are set to perform outside of established, hardwired industries.

Artificial Intelligence and Agriculture

From tractors to combines to irrigation pumps, agricultural equipment comes into contact with the many different variables that combine to create a healthy crop. When each piece of equipment is outfitted with sensors, and when those sensors collect data about climate, growth rates, yields and moisture, farmers can process the data to make predictions. These predictions can inform their insurance rates, their subsidies and their farm’s overall efficiency.

With many international start-ups exploring the uses of this technology on one of the man’s oldest lifestyles, some drawbacks begin to emerge. First, the technology is still in development which means that it has yet to become cost-effective. Second, only the biggest, industrial farms in middle America are making use of data-driven artificial intelligence. However, Mick Keogh of the Australian Farm Institute brings up the point that areas with limited resources as well as regions being affected by rapid climate change may find that big data and AI will help conservation efforts and increase productivity. Artificial intelligence sifts through data patterns, finding innovative ways to increase yields within nature’s constraints. In such situations, an investment in sensors, big data, and AI might be worthwhile.

Still, other innovators are looking at the ways “pragmatic AI” can improve or replace traditional farm labor. A Silicon Valley-based robotics company is exploring ways machines can harvest apples without compromising the fruit’s quality. By mapping the ways laborers move about fields, documenting the pressure placed on fruit and collecting biometric data, robots can “learn” how to pick apples.

Whether it’s in improving crop yields, optimizing resources or replacing inconsistent labor practices, the next industry jolted by disruptive technology just might be the one that puts food on our tables.

 

 

 

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