How Farmers Are Employing More Robots by Dr. Timothy Smith

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Successful, robust agriculture lies at the heart of human health and safety. Access to affordable food contributes to a tranquil population and a productive society. The American farmer remarkably produces enough food every year to feed 136% of the country's people, according to an article in the journal Current Developments in Nutrition. (nih.gov) Such a massive capacity to produce food depends on many factors, including deep agricultural know-how and science, automation, finance, and human labor. Labor shortages and rising supplies, equipment, and labor costs pose significant challenges to farmers every year. Relatively few, about 2%, Americans farm the land today, which stands in contrast to the 40% of Americans farming in 1900. Advances in mechanization and chemical herbicides and pesticides have made it possible for so few people to achieve such massive production.

The farms of today may have far fewer hands working on them, but human labor remains necessary to successfully bring produce to the market in good, fresh condition. Laborers help in planting, tending, and harvesting many crops. However, a strong job market and diminishing labor supply have pushed farmers to raise wages and health benefits to try to attract more labor to help on the farm, but often still they cannot find enough hands. Recently, a strawberry farm in Washington reported leaving a quarter of its crop to rot on the vine due to a shortage of available harvesters. (wsj.com) Farmers across America have for generations embraced new technologies to amplify their ability to farm more land with fewer people. The motorized tractor replaced the horse for tilling the soil, and the airplane helped to spray crops in minutes that would take a large group of people hours to do on foot.

In the same fashion, farmers of today have begun to turn to robotics powered by artificial intelligence to increase their productivity with fewer people. Bonsai Robotics, for example, produces a vision automation system that controls driver-optional harvesters that will work in orchards to harvest fruits and nuts. Bonsai claims its system improves job efficiency and effectiveness by 60%. (bonsairobotics) Another major problem for farmers lies in weed control. Weeds compete with crop plants for water, nutrition, and sunlight and can severely compromise yield. A company called Carbon Robotics has developed a robot that uses computer vision and deep learning to identify weeds and kill them with a laser. They claim that their robot can kill  300,000 weeds in an hour while covering 1-3 acres of land. They claim that their robot reduces hand labor costs and herbicide costs, thereby reducing farmers' weed control expenses by 80%. (carbonrobotics.com) A company named Allynav produces several different robots for agriculture that work in precision, autonomous applications such as orchard mowing in very uneven terrain with exceptional accuracy or precision pesticide application, saving tons of pesticide to reduce cost and protect the environment. Their robots can work at night and during the day to maximize efficiency.

As labor shortages continue to strain American agriculture, farmers will increasingly turn to robotic solutions powered by artificial intelligence to maintain high levels of productivity and cost reduction. In keeping with historical trends, modern farms increasingly rely on technology to bridge the labor gap. Several companies have sprung up to offer autonomous machines for harvesting, weed control, and precision pesticide application, boasting significant gains in efficiency and cost reduction. To be successful, this next generation of farm robots needs sturdy construction to withstand dusty, scorching, and rugged environments, currently only suitable for human labor. However, as automation reshapes farming, we need to remain sensitive to the dynamics of shifting labor markets—ensuring that innovation complements, rather than erodes, the social and economic fabric tied to agricultural work.

Dr. Smith’s career in scientific and information research spans the areas of bioinformatics, artificial intelligence, toxicology, and chemistry. He has published a number of peer-reviewed scientific papers. He has worked over the past seventeen years developing advanced analytics, machine learning, and knowledge management tools to enable research and support high-level decision making. Tim completed his Ph.D. in Toxicology at Cornell University and a Bachelor of Science in chemistry from the University of Washington.

You can buy his book on Amazon in paperback and in kindle format here.