Digital Farming and the Future of Agriculture

According to traditional agricultural practices, productive assets are described by soil variables that change slowly over time. Soil variables are more stable than digital farm information, which is invariant. As digital farming uses massive amounts of information, they move from invariant to variant.

This article will discuss the importance of digital farming and the various data and devices that can make this process easier and more efficient. Also covered are Augmented reality and Robotic process automation. Digital farming is the future of agriculture, and it will likely continue to change the landscape of farming in the coming years.

IoT devices

Using IoT in agriculture is a great way to improve efficiency and productivity in the agricultural industry. IoT devices help farmers make better decisions by monitoring specific operations and statuses.

For example, IoT in agriculture can help track the performance of fields and share insights with other areas. It is also much more affordable than other methods of monitoring and managing farm operations. Moreover, it can cover virtually every aspect of agricultural operations.

Digital Farming and the Future of Agriculture

The agriculture sector faces numerous challenges with a growing population, changing climate, and limited resources. For the agriculture sector to meet the challenge, it must increase its production volume by 50%.

However, conventional farming methods cannot meet this considerable demand. The only way to meet the need is to improve production efficiency. With smart farming, farmers can monitor crops and livestock and even monitor their population.

The IoT in agriculture technology is bringing incredible technological advantages to agriculture. For example, IoT-enabled drones can monitor livestock health and spray fertilizer in a fraction of the time it takes humans.

Unlike aeroplanes, drones are better suited to collect data and can fly over an entire field simultaneously. Another useful application for drones is in planting trees and monitoring crop health. The agriculture sector can also use drones for mapping and crop health analyses.

Robotic process automation

There are many challenges in agriculture and logistics today. One way to meet the growing demand for high-quality food and improved logistics is to automate these processes. Robotic process automation is an increasingly important technology for these industries.

It can help farmers make the most of their limited time and resources, improve their yields, and reduce the number of labourers they must hire. The following section will look at how the agriculture sector can use robots.

First, robotics and machine learning will partially automate certain physical activities, but there will also be a skills gap as new skills are needed to implement new technologies. This article will examine the skills gap related to automation in production agriculture.

This article discussed how robotics and machine learning will help farmers improve productivity and produce value-added products while reducing operating costs. It’s essential to recognize that the economic benefits of automation must be assessed across the entire farm system rather than a single technology at a time.

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First, robotic process automation improves the efficiency of tasks. By automating repetitive tasks, farmers and traders can free up time for other, more critical studies. This ultimately results in higher productivity and profits.

It also helps farmers monitor the prices of their crops and fields and helps manage the market and trade more efficiently. It also makes it easier to automate the process of marketing, production, and business. With more time to spend on other activities, farmers and traders can focus on other things.

Augmented reality

The potential for augmented reality in digital farming is vast. Farmers manually measure the fertility of their fields and monitor pests. With the help of AR technology, farmers can get information about the type of crop to grow on a particular piece of land.

They can also use it to determine which insects might cause a crop to become less productive. This kind of technology could improve the way we work and live in the future. It could reduce crop wastage and help farmers train other farmers better.

A typical example is the FarmAR app. This AR application allows farmers to monitor their farms remotely and updates its base maps to reflect vegetation and soil health changes. Users can even add notes and photos to specific locations to track the progress of a farm.

Digital Farming and the Future of Agriculture

With this technology, farmers can view the entire farm in one app and make intelligent decisions based on data that can help them optimize their operations. Further, farmers can analyze their land more efficiently with augmented reality apps.

The combination of AR with modern graphics has made this technology highly useful for farmers. With real-time AR training, farm personnel can learn on the go. By combining AR with monitoring technology, farmers can hire personnel with the basic skills to oversee their farms.

The sector can even use AR training to train workers to diagnose problems on the farm, reducing the time and cost associated with regular crop checks. Similarly, AR training can help farmers detect faults and breakdowns of farm machinery and make timely repairs.

Smart farm machinery

Agronomists and farmers are turning to new technologies for crop management. For example, advanced Farm Technologies Inc. has developed self-driving hybrid EVs and self-picking strawberry machines that use a stereo camera to detect when a berry is ripe.

The company has partnered with Kubota and Yamaha to bring its products to the market. As the company moves forward with developing new intelligent farm machinery, the future of farming will be bright.

The emergence of intelligent farming has raised questions about traditional farm practices’ cost, reliability, and environmental impact. However, with the advancement of technology, this method is already playing a crucial role in the productivity of farming.

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Intelligent farming has many benefits, ranging from reducing labour costs to lowering environmental impacts. While the adoption of innovative farming technologies is still in its infancy, these innovations are becoming increasingly common, albeit slowly.

For example, agricultural robots are already becoming common on farms. They can perform tasks such as planting, watering, harvesting, and sorting. Innovative farm machinery is already helping farmers produce more food and higher-quality crops with a small workforce.

The tractor, the heart of the farm, is the first machine to be autonomous. In the future, farmers will be able to operate this machine without human supervision remotely.

AI on sparse data

Agricultural productivity can be optimized using data-driven techniques, such as artificial intelligence, to improve efficiency and minimize losses. While these methods have many advantages, they are still widely underused due to limited connectivity and the high costs of collecting data by hand.

This Webinar discussed innovations in digital farming that use the Internet of Things (IoT) and artificial intelligence. The Webinar also covered an Azure FarmBeats demonstration, illustrating how AI can improve the efficiency and productivity of farming operations.

Agricultural AI is becoming more advanced and versatile as we move from analogue to digital agriculture. It can help increase efficiency and improve crop yields by predicting water, energy, and fertilizer use. But it is also highly prone to failure, making it challenging to implement AI on sparse data in digital farming.

However, the benefits are far greater than the risks. The agricultural sector can use AI to forecast power demand and energy consumption in net-zero buildings. African researchers are also interested in this field. The continent is well-positioned to provide data for AI applications since over 50% of its workforce is employed in agriculture, much of which is subsistence level.

For decades, the African continent has been of intense interest to local and international stakeholders. Moreover, data on African agriculture is available from multiple sources, including the African Soil Information Service (ASIS).

Markets

The global digital farming markets are highly fragmented, with smaller players competing with big firms for market share. Major revenue-generating players include

  • IBM Corporation
  • AGCO Corporation
  • Hummingbird Technologies

Other prominent players include

  • Gamaya SA
  • Bayer CropScience

Most companies focus on product launches and aggressive acquisition strategies, while others innovate through partnerships. These factors will ultimately shape the future of the digital farming markets. Let’s take a closer look at the various regional segments.

A new study published by Market Research Culture provides a global assessment of the Digital Farming markets. It details the market’s size, trends, and forecasts through 2027. It outlines essential market research data, making it an invaluable resource document for key industry players.

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It also features an in-depth analysis of competitive dynamics in the Digital Farming market. This report provides insight into the trends and drivers driving the growth of this market. Furthermore, it identifies future business opportunities and challenges.

The Digital Farming market was segmented into five major regions: Europe, North America, Latin America, Asia Pacific, Middle East, and Africa. North America led the global market in 2019 and is predicted to continue dominating the market over the forecast period.

This region is primarily driven by a significant investment in advanced agricultural techniques. Moreover, the presence of major players in each area is expected to foster growth in the Digital Farming market.

Skills

With the increasing use of digital technologies, digital farming skills have become integral to farm management. Regulatory requirements are also reflected in the need for farmers to have these skills. For example, by 2018, the EU Commission requires BPS applications to be submitted online.

In addition to addressing regulatory requirements, digital skills help farmers understand and assess their own farm business. The following are some essential skills for a digital farmer.

These skills include

  • Critical thinking
  • Creativity
  • Complex problem solving
  • People management
  • Emotional intelligence
  • Coordinating with others
  • Judgment and decision making
  • Negotiation
  • Service orientation
  • Cognitive flexibility. Learn more

Developing new digital farming skills is a crucially important part of SEED. In addition to promoting employment in the agricultural sector, SEED also supports the development of a Joint VET Qualification (JVQ) in digital farming.

Developed by SEED, the digital farming skills will be mapped against existing competencies and frameworks, such as DigCOMP and EntreCOMP. The project also aims to develop an entrepreneurial and work-based learning component into the project.

As the sector transitions towards digital farming, a critical shortage of digital skills persists. Despite this, EU-funded projects are helping lead the digital change by encouraging farmers to share knowledge and compile a digital tools database.

In addition, a DESIRA project assesses social, economic, environmental, and governance variables. It is critical to provide up-skilled training for farmers to take advantage of new digital technologies and increase agricultural productivity.

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Digital Farming and the Future of Agriculture
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