A leap forward in Ag-Tech: how autonomous systems and precision agriculture are transforming farming – a guide

Table of Contents

• What is driving the adoption of autonomous farming equipment?

• What can be expected from the autonomous farming equipment market?

• Precision agriculture for a deeper understanding of the farm environment

  • Artificial Intelligence (AI) is coming to the farm

• A glimpse at some of the navigation sensors and technologies used in autonomous agriculture

  • ISO 11783 – piecing together the ag-tech jigsaw

• Economic advantages of autonomous agriculture

What is driving the adoption of autonomous farming equipment?

Farming is a hands-on vocation requiring dedication, resilience, skill and stamina that is often overlooked in terms of its critical importance to society. As populations increase and there are ever more mouths to feed, a groundswell of recognition for what is being termed “food security” is being felt across the world. Farmers are expected to sustain increasing populations and provide for broader dispersion of produce, so require new methods to achieve this. Traditional techniques for crop growing and other agriculture activities have been a mainstay for literally centuries, however, technology has caught up in a big way that is offering farmers many new and ingenious ways to improve life on the land. Concurrently, populations are tending to become increasingly concentrated in urban areas and, as a consequence, away from farm work. This is leading to further pressure on farmers and their precious resources. Farmers face several obvious challenges:

• Increasing yield per hectare of land.
• Reducing labour availability.
• Managing land for long-term sustainability, taking into account greenhouse gas emissions, climate change and changing regulations.
• Sustaining operations despite dwindling workforce availability.

To overcome the above and many other challenges facing the agricultural community, new technologies and practices are required to replace particularly mundane and labour-intensive tasks and freeing up time for other work. This results in a shift in farming and agriculture practice to automate labour and machinery intensive practices through the adoption of autonomous systems.

Mounting pressure is also on farming to alter practices in ways that can help stymy the effects of climate change and reduce greenhouse gas emissions. This is no easy task, especially when coupled with increasing output, but challenges that can be helped overcome using autonomous farming equipment, robotics and clever science.

Agriculture is facing other crises. The movement of people from rural to urban areas not only leaves a labour shortage problem, but more prominently, a succession problem. As a result, the average age of farmers is increasing – this is due to children typically being less interested in farming, which creates the problem of who will work the farm when the current generation of farmers retire. The answer may lie in the very field of modern ag-tech – the potential for robotics and autonomous farming equipment and management systems is changing farming from what was once a laborious, demanding and repetitive vocation into an industry that is not only rapidly adopting the latest sensor, robotics and autonomous technologies, but also playing an important role in driving research and development in them.

This paradigm shift in agriculture from relatively low-tech to latest-tech is sure to inspire youngsters that otherwise might leave the farm to pursue city jobs, to stay on the farm and be part of a new generation of farmers that use and help develop cutting-edge agriculture technologies.

Autonomous tractors and harvesters can operate day and night.

What can be expected from the autonomous farming equipment market?

Primarily, autonomous farming technologies exist to free up human farm workers from certain activities, where their time can be better spent on more important things . Currently, these aids are typically machines that are equipped to perform specific, regular tasks. The most obvious is the tractor, which is used for numerous jobs on a typical crop field. These may include tilling, seeding, cultivating and harvesting; with the tractor traversing the field in a regular lawn mower pattern each time. The boundaries of a field and the simple notion of driving up and down it are ideal for automation.

Existing tractors can be retrofitted with self-driving systems to save on recapitalisation, with manufacturers also offering autonomous tractors and other equipment “out of the box”. To assist farmers in managing capital expenditure and more efficiently distribute the resources spent in equipment manufacturing, autonomous tractors and autonomous farming equipment can be temporarily leased during times of high demand via companies offering farming and robots as a service (FaaS and RaaS, respectively) models.

Specialised robots are also coming to market for niche or specialised farming applications, such as Naïo Technologies’ Ted vineyard robot.

Other big advantages of using autonomous farming equipment are that time of day, shift length and downtime due to operator breaks or illness become things of the past.

Precision agriculture for a deeper understanding of the farm environment

How to define precision agriculture (PA)? It is a tech-based methodology designed to provide farmers with a clear, in-depth understanding of farm conditions. The key concept underpinning PA is to use detailed observation and measurement for what might be termed “strategic farming”. The greater the number of variables being measured, the larger the available data. When the data can be intelligently analysed and linked, farmers can better understand the soil, where and when to plant various crops and how to tend them for sustained output.

For example, measuring soil moisture content, topology, rainfall, sun exposure, oxygen and nitrogen content that is coupled with precise locations of where measurements are taken gives farmers a new insight into what is happening above the soil and in it. Using this data, farmers can make more informed decisions that are very specific to particular conditions or crop needs. As an example of how this can alter farm activities, prior to precision agriculture, farmers would spray entire crops as fairly standard practice – a blanket approach. With precision agriculture, only areas that require spraying are sprayed (perhaps using autonomous Unmanned Aerial Vehicles – UAVs). The increases in efficiency and the minimisation of resource use and chemical applications are obvious.

A recent study on the benefits of precision agriculture by the Association of Equipment Manufacturers (AEM) in the United States found the following:

• +4% crop production.
• +7% fertiliser placement efficiency.
• -9% herbicide and pesticide use.
• -6% fossil fuel consumption.
• -4% water consumption.

The above indicators are just the beginning of a new direction for large-scale farming. It is clear that precision agriculture and autonomous farming equipment are mutually beneficial. Industry pundits suggest that the adoption of precision agriculture practices and autonomous farming equipment will significantly further these already positive results.

Precision agriculture provides farmers with detailed insights into the state of the land and crops. Farmers can use this data to make well-informed decisions.

It is very possible that future agriculture may include farms that operate entirely autonomously, with many machines, both on land and in the air. These machines will communicate using a common interface with a control system that employs artificial intelligence and machine learning (ML) to coordinate activities, and adjust and self-regulate farming operations with unprecedented levels of efficiency.

Artificial intelligence (AI) is coming to the farm

Artificial intelligence (AI) is being leveraged to make autonomous systems smarter and more useful. For example, AI-enhanced sensor suites can enable robots to detect and avoid obstacles and people, operate within strict boundaries and improve operational efficiencies; even judging whether the terrain ahead can be safely traversed.

AI has much more to offer farmers than vehicle navigation and control. The advent of precision agriculture and using other modern-day technologies, such as uncrewed aerial vehicles (UAV or “drone”), enables farmers to survey farms and crops without having to physically visit sites, saving much time, money and resources. The AI can be used to process the survey data (for example, images, LiDAR) to identify specific objects or phenomena and provide high-accuracy location data so that weeds or diseases, for example, can be responded to.

AI-enhanced robots can scan an image of a fruit and determine if it has the necessary properties for picking, such as ripeness, colour, size and condition. It can do this in a fraction of a second before performing the actual picking, minimising sorting and handling further down the line and leaving behind fruit that is not ready for harvest or otherwise does not meet quality standards. Similarly, weeds can be automatically identified and targeted for spraying or extraction, helping minimise the use of herbicides and pesticides.

Autonomous agriculture robots with AI assistance and control can evaluate fruits and vegetables before performing the actual picking.

A glimpse at some of the navigation sensors and technologies used in autonomous agriculture

• Autonomous systems and robotics rely on many types of sensors to provide the necessary input data for correct and safe control. A navigation system is at the heart of any autonomous system that relies on movement for operation. Accurate positioning is critical for safe operation and, in the case of autonomous tractors, vital for performing operations in the correct field or area.
• Uncrewed Aerial Vehicle (UAV) surveying for inspection and precision agriculture applications also require a navigation system; not only for controlling the trajectory of the vehicle but to provide accurate georeferencing (longitude and latitude coordinates) that is necessary for pinpointing the exact positions of items of interest. A navigation system will typically use GNSS (navigational satellites) and related technologies to provide georeferencing data.
• Autonomous tractors will employ various sensors for identifying objects in the surroundings. These may include cameras, where the collected imagery is processed in real-time using artificial intelligence (AI) that is trained to recognise various objects by shape and size, from which appropriate action can be taken. Infra-red cameras can enable night operation and also “see” people and animals via their heat signatures.
• For precision agriculture, a raft of ground-based and airborne sensors can be used for various purposes. Topological and ground survey often uses LiDAR (light detection and ranging) sensors that can be used to create accurate digital models of the land, objects on the land, and vegetation. In and on the ground sensors are available for measuring soil moisture, nitrate concentration, pH level, ground and sub-ground temperature, air pressure, relative humidity and many other important criteria.
• Advances in robotic control and precision movement enable “intelligent robotic arms and hands” to accurately and carefully pick and handle delicate produce. Electrification of power systems reduces immediate carbon emissions and is also helping miniaturise some vehicles – lighter vehicles compact the soil far less than some traditional heavy equipment, which is vital to maintaining well-aerated soil that is capable of holding moisture for longer. The adoption of autonomous and precision agriculture will only further boost research and development into ever more sensitive and useful sensors and purpose-designed autonomous farming equipment.
• Autonomous UAV drones can be used to drop seed rapidly over large areas using georeferencing data for accurate placement. Similarly, highly efficient and targeted spraying and aerial depositing can be accomplished that applies herbicides, pesticides, fertilisers with the least waste and only in areas where it is needed.

ISO 11783 – piecing together the ag-tech jigsaw

Individual autonomous vehicles, robots and other agricultural machines are great in isolation, but to manage them all with centralised and interconnected efficiency will make each individual solution markedly better in terms of achieving overall, coordinated autonomous agriculture. To this end, ISO 11783 (also known as “ISObus”) exists as a means of standardising a communications interface for interconnecting agricultural equipment, sensors and control systems. To quote part of the standard:

A standardised communications protocol will enable compliant equipment from different manufacturers to communicate and inter-operate seamlessly. ISObus also supports high voltage/high energy electrical connections for powering equipment.

Economic advantages of autonomous agriculture

Autonomous agriculture robots, autonomous tractors and autonomous farming equipment will help overcome many of today’s agronomic challenges.

• Coupling autonomous systems, robots, artificial intelligence and machine learning capabilities with precision agriculture practices greatly assist farmers in better and more fully understanding the nature and properties of the land they till, plant and harvest to sustainably extract the most out of the land, season to season.
• Gathering data on the properties of the soil, sun exposure, moisture and chemical content amongst other useful information greatly assists in planting crops that are best suited to the prevailing conditions and produce the biggest crops. Larger crops, better quality and higher efficiency will not only make farming more economically profitable, but also effectively deal with higher output demand, assist in crop diversity, and comply with increasingly stringent regulations.

Note that because autonomous systems and their use in agriculture are still new, many jurisdictions throughout the world have regulations that control the application of autonomous agriculture. For example, how much human supervision of autonomous vehicles is required and whether drone-based spraying of herbicides is permitted.