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Precision agriculture is a key component of the third wave of modern agricultural revolutions. The first agricultural revolution was the increase of mechanized agriculture, from 1900 to 1930. Each farmer produced enough food to feed about 26 people during this time. [18]
Emerging digital technologies have the potential to be game-changers for traditional agricultural practices. The Food and Agriculture Organization of the United Nations has referred to this change as a revolution: "a 'digital agricultural revolution' will be the newest shift which could help ensure agriculture meets the needs of the global population into the future."
The new research unites technology with farming expertise to develop diverse agricultural landscapes based on natural ecosystems. "One [method] would be sensing.
The FAO-ITU E-agriculture Strategy Guide [30] was developed by the Food and Agriculture Organization and the International Telecommunication Union (ITU) with support from partners including the Technical Centre for Agricultural and Rural Cooperation (CTA) as a framework for countries in developing their national e-agriculture strategy/masterplan.
Robotic farming, particularly urban and indoor, is the focus of a U.S. Department of Agriculture three-year grant-funded project at University of Maryland Eastern Shore.
An agricultural robot is a robot deployed for agricultural purposes. The main area of application of robots in agriculture today is at the harvesting stage. Emerging applications of robots or drones in agriculture include weed control, [1] [2] [3] cloud seeding, [4] planting seeds, harvesting, environmental monitoring and soil analysis.
FarmWise Labs, Inc. (established 2016) is an American agricultural technology and robotics company, based in California.Its first product is an automated mechanical weeder that uses a combination of AI, computer vision and robotics to pull out weeds in vegetable fields without using chemicals.
In agriculture, data mining is the use of data science techniques to analyze large volumes of agricultural data. Recent advancements in technology, such as sensors , drones , and satellite imagery , have enabled the collection of large amounts of data on soil health , weather patterns , crop growth, and pest activity.
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