Industry Voices: Agricultural Automation Will Feed the World

With an expanding world population and a plateau in farm worker growth, a crunch will soon come between food needs and food production. The solution will likely come via automation technology. The World Economic Forum released a report this year noting that automation is helping farmers lower costs, improve efficiency, reduce their environmental impact, and address labor shortages. Technological advances in areas such as artificial intelligence, robotics, and sensors make automation more feasible and affordable.

We caught up with Sarah Schinckel, director of emerging technologies at John Deere to get details on the type of technological advances that can bring down costs while expanding yield in the agriculture industry.

How will a fully autonomous operation help farmers feed, fuel, and clothe the world?

Sarah Schinckel: The world population is expected to grow from 8 billion to nearly 10 billion people by 2050. This will require farmers to double their food production to meet the needs of the increased population and the demand for improved diets. At the same time, the US Bureau of Labor Statistics estimates that between 2019 and 2029, the agriculture workforce will grow only 1%, the slowest of any profession. Adding to that, the average US farmer is 55 years old and works long days, usually 12-18 hours. While today’s farmers have deep expertise about their land, equipment, and the crops they grow, they also face many conditions outside of their control. Weather variability, soil conditions, input prices for seed and fertilizers, and crop sale prices all impact a farmer’s ability to grow the food, fuel, and fiber the world needs. How will farmers overcome these challenges? Precision technology, including autonomous machines, helps farmers meet this increased demand in the face of variability and staffing shortages.

A farmer grows crops through a series of steps: preparing the soil, planting seeds, nurturing the growing plants, and harvesting the mature crop. As mature crops are harvested, farmers immediately transition to preparing the fields for the next season’s crop. They do this by using tillage equipment to turn over the soil, readying it for the next season’s seeds. But because most farmers manage multiple fields, they’re simultaneously harvesting crops and preparing the soil. This means they’re often doing two steps at once, requiring additional resources to get the job done. Technology helps farmers manage this increased workload. The John Deere fully autonomous tractor for tillage uses advanced technology like GPS, machine learning, computer vision, sensors, and connectivity to understand its surroundings, collect real-time data, and navigate through a field while performing precise tasks. This machine gives farmers time to focus on other areas of their business with confidence that the fieldwork will be done with precision and efficiency. And because these machines can operate longer hours than those driven by humans, autonomous machines improve overall productivity. 

Why is advanced connectivity important for autonomy? How will it expand in the coming years?

Sarah Schinckel: Connectivity is critical for autonomous field operations as real-time data sharing lets farmers monitor the equipment operating in their fields. The cameras and sensors on the machine are continuously collecting data – from video feeds to sensor readings – and this data is shared with farmers in the John Deere Operations Center (Operations Center), an opt-in cloud platform. From these applications, farmers can remotely manage operations and equipment, like starting and stopping machines, viewing live video feeds, monitoring fuel levels and task completion progress, and determining whether a machine should proceed when it encounters something unexpected. This remote management is only possible if machinery is connected.

Improving rural connectivity is essential to bringing autonomy to farms globally. Satellite connectivity will connect farms that are out of reach of today’s cellular networks. It will also help farmers leverage more technologies, share data between machines, remotely monitors operations, and ultimately, increase efficiency and productivity to grow more with less. 

John Deere envisions a fully autonomous farm by 2030. Explain what functions will be autonomous.

Sarah Schinckel: At John Deere, we’re already helping farmers prepare soil autonomously. Our goal is to bring autonomy to the other steps of the corn and soybean production cycle by 2030. Just like we introduced the autonomous tractor for tillage, we are continuing to work towards autonomous equipment for tasks within the planting, spraying, and harvesting steps. By continuously integrating advanced technologies like robotics, artificial intelligence, and sensors into our machines, we’re helping our customers meet the global demand for food, fuel, and fiber.

What is the role of data sharing and cloud platforms in autonomous agricultural operations?

Sarah Schinckel: Data is foundational to an autonomous system. Technologies like sensors, cameras, and GPS receivers generate data that become inputs to machine learning and control systems. This is the basis of automating machine functions. Data also acts as feedback to farmers about how fieldwork is progressing, how much seed or product is being applied to a field, or what yields are being harvested from a mature crop.

With connectivity, data is seamlessly transferred between machines and the cloud, enabling farmers to view data in the Operations Center web and mobile applications. Farmers use the platform to create work plans, manage logistics, and monitor real-time fieldwork. They can also use tools within the Operations Center to analyze their operations and gain insight into the overall productivity and efficiency of their business. Analysis tools let farmers compare fields, review year-over-year performance, and use data to optimize decisions and strategies for the next crop season. 

How does data visualization help farmers become more productive?

Sarah Schinckel: Data visualizations make it easy for farmers to digest large amounts of data. This in turn informs them of what actions they need to take to ensure a successful current and future season. An example from the Operations Center is a yield map. A yield map shows how much crop was harvested from any given point in a field. By combining thousands of data points into a single visualization, a yield map makes it easy for farmers to see the higher and lower-yielding areas of their field. From there, a farmer may decide to make different decisions about how many seeds to plant in an area of the field or how many nutrients to apply in a given area. Visualizations make data usable and actionable, helping farmers manage their complex businesses. 

Explain how remote monitoring can help farmers engage in more sustainable practices.

Sarah Schinckel: Connected machines can seamlessly share data with the Operations Center platform and with other machines working in the same field. Farmers can operate one machine and get real-time data about what another machine is doing. On a sprayer, remote monitoring and data sharing, combined with GPS technology and control systems on the equipment, alert machines on where another machine has already applied nutrients in a field. As a result, the machine doesn’t re-apply nutrients, resulting in fewer chemicals used and higher cost savings. For a farmer, this is a sustainability advantage powered by data and technology.

Remote monitoring and data analysis tools in the Operation Center also allow farmers to gain insights into carbon intensity, soil health, and fuel emissions using recently introduced sustainability tools.  Farmers can use the tools to optimize sustainability practices and enroll in voluntary revenue-generating programs.