Editorial Feature

Is AI the Future of Autonomous Agriculture?

Agriculture equipment manufacturer John Deere recently launched the world’s first production-ready autonomous tractor, supported with artificial intelligence (AI) technology by technology startup SparkAI. This article examines the role of AI in agriculture today.

Image Credit: Suwin/Shutterstock.com

AI, Automation, and Agriculture

In 2023, AI and automation have become a feature of everyday life.

Businesses in many sectors use AI technologies such as artificial neural networks (ANNs) and large language models (LLMs). Sectors like manufacturing and logistics have embraced industrial automation. Despite its bucolic image, agriculture is also at the cutting edge of applying these new technologies.

Such a development is in part because of several challenges facing food production around the world right now. The planet’s human population is forecast to reach 10 billion by 2050, and absolute rates of poverty are decreasing. As a result, the demand for food is expected to increase by 50% in the next three decades.

At the same time, climate change, dwindling stock of arable land, and pressures in the labor market are making it increasingly difficult to farm productively. Crop yields are diminishing, soil quality is declining, and biodiversity essential for healthy ecosystems is under threat.

Taken as a whole, climate change is responsible for removing 35 trillion consumable food calories from supply each year. This is especially dangerous for poorer countries that cannot afford to import food and are typically the worst affected by climate change and global warming.

Agriculture, as well as being impacted by climate change, also contributes to it. Land use changes for agriculture cause widespread deforestation and contribute nearly half of all methane emissions.

AI and automation could hold the key to overcoming these existential threats. Improving productivity and efficiency in agriculture can make food production less environmentally harmful and more adaptable to the world’s changing needs for food products.

SparkAI Provides AI Solutions for Autonomous Agriculture

SparkAI was founded by engineers from top self-driving car programs such as Zoox and UberATG. The founders recognized that improving AI systems would help automation providers get through technological bottlenecks and deploy more and more effective automation processes across industrial sectors.

The company has generalized an AI solution initially developed to enable self-driving cars to deal with unexpected real-world driving conditions. The AI products are now available for a number of automation applications via the company’s lightweight application programming interface (API).

SparkAI uses machine learning (ML) algorithms to resolve exceptions in real-time, powering “intelligent” decision-making by autonomous machines. ML is simply the application of computer processing to analyze and respond to a machine’s own outputs to affect the machine’s future behavior.

SparkAI is used in production AI workflows in agriculture to make technologies like robot harvesters and self-driving tractors work effectively in real-world conditions.

John Deere Launches World-First Production-Ready Autonomous Tractor

John Deere is a globally recognized brand that manufactures and supplies heavy farm equipment and plant machinery around the world. Alongside SparkAI, the company recently launched the world’s first production-ready autonomous tractor.

The tractor is equipped with a 360-degree obstacle avoidance system incorporating multiple stereo camera arrays and a range of other sensors. This system continuously feeds data into an ANN (a kind of AI program that distributes processing tasks in a way analogous to the way synapses distribute electronic signals in biological brains) that classifies obstacles and decides on the best response to them.

Autonomous tractors must perform well and consistently in harsh conditions such as heavy rain, snow, dust, and bright sunlight. The environment in a farmed field is constantly changing as crops are seeded, grown, and harvested throughout the seasons.

These factors have previously made it difficult for ML models to make safe decisions autonomously and consistently. However, John Deere’s partnership with SparkAI is a significant step toward solving the problem of autonomous agriculture.

How Does AI Make Autonomous Tractors Work?

Image Credit: ART STOCK CREATIVE/Shutterstock.com

How Does AI Make Autonomous Tractors Work?

SparkAI’s model augments AI decision-making with human thought processes to provide machines with a “cognitive bridge” that they can use to deduce the best response to unique, unexpected challenges in real-world conditions.

When on-board and the AI cannot provide answers with enough confidence, the autonomous tractor automatically contacts the SparkAI service and provides imagery and metadata to the company’s central API. Then, human operators supported by the SparkAI program resolve the problem and provide new instructions for the tractor in the field.

With AI supporting human operators, this entire process takes place in just a few seconds and the tractor is quickly on its way again.

Is AI the Future of Autonomous Agriculture?

This latest launch by John Deere and SparkAI is just one example of a number of recent applications of AI in autonomous agriculture.

For example, farmers are already using AI for targeted agriculture, controlling crop moisture, soil composition, and temperature in food-growing areas precisely to optimize production levels and crop yields.

An Israeli technology company recently used AI to optimize light and water conditions so crops could be grown in small containers that fit inside a regular urban residence. This technology would help turn cities into food production sites and reduce the need for land use changes and deforestation. It would also enable urban dwellers in developing countries to take more control of their own food production and increase food security.

The AI technologies currently being developed can identify and precisely target weeds in fields, eliminating them with just the right amount of herbicide and reducing risks of chemical run-off and pollution of local ecosystems.

Agriculture must adapt to meet the world’s increasing need for food in the next few decades. AI and industrial automation may hold the keys to that adaptation and may become the new normal in farming in the near future.

Continue reading: The Benefits of Drones to the Agriculture Industry

References and Further Reading

Solving the Last Mile of Autonomous Farming. Spark.ai. Available at: https://www.spark.ai/blog/solving-the-last-mile-of-autonomous-farming

Young, S. (2020). The Future of Farming: Artificial Intelligence and Agriculture. Harvard International Review. Available at: https://hir.harvard.edu/the-future-of-farming-artificial-intelligence-and-agriculture/.

Disclaimer: The views expressed here are those of the author expressed in their private capacity and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork the owner and operator of this website. This disclaimer forms part of the Terms and conditions of use of this website.

Ben Pilkington

Written by

Ben Pilkington

Ben Pilkington is a freelance writer who is interested in society and technology. He enjoys learning how the latest scientific developments can affect us and imagining what will be possible in the future. Since completing graduate studies at Oxford University in 2016, Ben has reported on developments in computer software, the UK technology industry, digital rights and privacy, industrial automation, IoT, AI, additive manufacturing, sustainability, and clean technology.


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