Steady Growth of AI in Agriculture Forecast

Robert Woolliams

June 12, 2017

3 Min Read

Agriculture is perhaps not the first industry you would associate with artificial intelligence. However, Technavio market research analysts forecast the global artificial intelligence (AI) market in the agriculture industry to grow at a CAGR of close to 23% during the forecast period, according to their latest report.

The market study covers the present scenario and growth prospects of the global AI market in the agriculture industry for 2017-2021. The report also lists robotics, crop and soil management, and animal husbandry as the three major application segments, of which the robotics segment accounted for more than 42% of the market share in 2016.

Technavio analysts highlight the following three market drivers that are contributing to the growth of the global AI market in the agriculture industry:

  • Maximizing profits in farm operations

  • Higher adoption of robots in agriculture

  • Development of deep-learning technology

Maximizing profits in farm operations

Incorporation of AI technology in the form of robots, drones, crop management systems, and herd management tools enable farms to increase the yield and output of crops and animals and maximize profits in farm operations.

Smart or precision agriculture is rapidly emerging as a technology that will help farmers to enhance the deliverables in agriculture. With AI technologies on the rise, farmers can control and monitor the equipment, crop, and livestock through their smartphones and receive statistical predictions for crops and livestock.

“Smart sensors, satellite imagery, and other cloud-based technologies are highly beneficial to observe and record data during crop planting and harvesting, thereby maximizing production output and minimizing wastage of resources,” says Bharath Kanniappan, a lead analyst at Technavio for automation research.

Similarly, in animal husbandry, advanced AI technologies can be used to monitor and analyze the health and physical well-being of animals and flag deviations in case of any disease or ailment. In this way, animals can be treated in due course of time without spreading the infection to other animals. Such timely monitoring saves money, as it enables precautionary intervention of an issue in the early stages before it becomes a widespread epidemic.

Higher adoption of robots in agriculture

The use of robots has increased in the agriculture and dairy farms due to the advantages they offer in terms of time, enhancement of control and reliability. Robots are highly efficient entities that display higher capability in carrying out multiple tasks within a shorter time frame.

“Deployment of robots in agriculture helps to ease the burden on farmers who can now adopt a supervisory role. In addition, the reduction in the number of manual labor would help to cut down on expenses and thereby generate higher profit in farm operations,” says Barath.

Robots deployed in farms can display a better control in terms of data collection. The use of robots in farm applications increases the quality of output, as humans do not possess an ability to match the same precision as that of the robots. Moreover, robots deployed in the farms are equipped with advanced sensors and vision systems making them highly reliable entities for taking decisions.

Development of deep-learning technology

Deep-learning software is one of the most advanced versions of AI technologies as it attempts to mimic the activity and functioning of the human neocortex, the most active part of the human brain. The software is capable of learning to recognize patterns of sounds, images, and other data. At present, it is being deployed in industrial robots to empower their learning ability and train other robots.

Advanced technologies like deep learning technology require supercomputers with high speeds and capacity to explore its full potential and development. Japan is making substantial investments to regain momentum in the field of automation, especially AI technologies.

Article republished from:

Feature image credit: Pexels

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