Figures on the Economic Strength of Agriculture
In 2022, agriculture in the EU accounted for just 1.4 percent of the total gross domestic product. From 2005 to 2020, the area of land used for agriculture in the EU fell by 37 percent. Over 5 million farms have given up agricultural production. Almost 4 million people work in agriculture in the EU. In the course of agricultural industrialization, the majority of farms are large farms with an area of over 100 hectares. Just under 6 percent of all agricultural businesses still operate a farm with an area of less than 5 hectares.
Overall, agriculture is an industry full of risks. Depending on the weather and environmental influences, as well as weather disasters, it is difficult to make clear forecasts and forward planning for agricultural processes and crop yields. Subsidies in the agricultural sector are intended to mitigate this challenge.
Smart Agriculture in the European Union (EU)
The area of land used for agriculture in the EU accounts for around 40 percent of the total land area. The value of gross production in the agricultural sector of the economy amounted to 449.5 billion Euros in 2021. This includes crop production (55.3 percent of the total value), livestock production (36.3 percent), agricultural services (4.8 percent) and non-agricultural goods and services (3.6 percent).
The average share of the agriculture industry’s gross value added in the EU’s gross domestic product was only around 3.10 percent. These figures do not adequately reflect the great importance of agricultural businesses as suppliers to the food industry. Furthermore, the efforts to ensure the quality of agricultural production and promote healthy nutrition are not clear.
Forecasts for IoT Growth in Agriculture
According to the OECD-FAO Agricultural Outlook 2023-2032, the global population will increase from 7.9 billion in 2022 to 8.6 billion in 2032. By 2032, the changing energy and food requirements of a growing and more affluent global population are expected to drive demand for agricultural commodities.
According to a report by Precedence Research, the global market for the Internet of Things (IoT) in agriculture will reach 13.61 billion USD in 2022 and is expected to grow to around 33.57 billion USD by 2032. A growth of 9.50 percent is expected between 2023 and 2032. In 2032, the IoT-based monitoring sector is expected to exceed 8 billion USD worldwide, while the intelligent sensor systems sector is forecast to reach 3.2 billion USD. Furthermore, the global agricultural drone market is expected to exceed 2.21 billion USD by 2032.
In 2022, the Asia-Pacific region will account for the largest revenue share of the global agricultural IoT market at around 44 percent. According to a report by ‘Allied Market Research’, the precision agriculture sector has emerged as the dominant force in the IoT market for agriculture in 2021. The software sector is a major player in the global IoT market for agriculture in 2021, offering a wide range of hardware control tools, including yield monitors, soil sensors, water sensors, and climate sensors used in precision agriculture, smart greenhouses, and fish farming.
Is There a Specific Kind of Agriculture?
There is no one specific type of agriculture. Agriculture is an industry in which food, animal feed, and agricultural products are manufactured. It quickly becomes clear that the agricultural sector consists of numerous sub-sectors. These sub-sectors include arable farming, wine growing, livestock farming, forestry, fishing and aquaculture, horticulture with a focus on vegetable cultivation, agricultural technology, fertilizer and pesticide manufacturers, the food industry, the beverage industry, logistics, research institutes, and political institutions.
It is clear that the integration of digitalization for companies and wireless IoT technology, with the aim of implementing IoT platforms and automation, depends heavily on the respective sub-sector of the agricultural sector. Opportunities for digitalization, such as the agricultural supply chain or the use of asset tracking, are available.
The Digital Agricultural Office
Farmers are obliged to prepare a large number of reports. These include the documentation of the pesticides and fertilizers applied, the health status of livestock, the administration of medication, and the harvesting processes. Consulting companies have become specialized in accompanying farmers on their way to becoming digital agricultural offices. E-learning courses show the first steps towards a paperless office.
This example clearly shows that agriculture has not yet arrived in the age of Industry 4.0. Farm management is still largely paper-based. However, economic forecasts assume that the agricultural industry will be a growth market for digitalization solutions and wireless IoT technology in the future. Without sensor-based solutions, targeted irrigation, cost-optimized pesticide application, environmental regulations, and soil quality measurement will not be possible. Smart Farming IoT stands for innovative digitalization solutions with telematics, cloud computing, and the Internet of Things.
Wireless IoT in Agriculture in Short Supply?
So far, innovative wireless IoT solutions have tended to be exceptions that attract a lot of attention because their goals are so obvious: Using less water, applying fewer pesticides to fields, increasing yield quality, and promoting animal welfare. Overall, the integration of wireless IoT technology into production in agriculture is a challenging task. This will be shown in the next sections.
The situation is quite different in other areas of agribusiness, such as the production of agricultural machinery, the processing of agricultural raw materials into food or the production of chemical additives for agriculture. Although these sub-sectors are directly related to agriculture, they belong to industries in which wireless IoT solutions are already much more prevalent.
These are the automotive industry, the chemical industry, logistics (container management, load carrier management), and the food industry. Compared to pure agriculture, these industries are more digitalized and automated. The overall view of the agricultural industry with regard to wireless IoT technologies, digitalization, and automation must therefore be very differentiated.
Wireless IoT Technology in Agriculture
Radio-Frequency Identification (RFID) enables animals and objects to be identified and tracked via radio waves. This is used for monitoring livestock or the supply chain of products, for example.
Sensors are used in various applications, such as condition monitoring. Soil moisture, humidity, temperature, pH, and other environmental conditions are measured to support decisions related to irrigation, fertilization, and other agricultural practices.
How does 5G work in agriculture? 5G can be used in agriculture for fast and reliable data transmission in real time. This is used for the remote control of machines, the monitoring of fields, or for the use of drones, for example.
Wireless Local Area Network (WLAN) is used on farms for the wireless networking of devices and systems in confined areas such as buildings or greenhouses.
Near Field Communication (NFC) technology can also be used in agriculture. NFC tags can be attached to livestock to store information such as animal health, vaccinations, feeding history, and other relevant data.
Products Designed for the Agricultural Sector
Important wireless IoT solutions and products in agriculture also relate to cloud computing, IoT, and big data in agriculture. Based on sensor data, big data solutions, and IoT, asset management in agriculture, container management, load carrier management, and the cold chain can be significantly optimized. The result is next-generation IoT smart farming. If 5G is available, the transmission of large volumes of data within the farmland can also be guaranteed.
A selection of wireless IoT products
The Importance of Yesterday and Today’s Agriculture
Agriculture is one of the oldest producing industries in human history. For most of human history, agriculture has been the engine of progress and infrastructure development. Logistics and retail were primarily used for the transportation and exchange of goods, agricultural products, and livestock.
In the course of the industrial revolution, however, agriculture became less significant as an economic sector. Other branches of industry and the service sector became increasingly important for society. With organic farming, agriculture and the production of high-quality food are once again becoming more important, and with it the status of agriculture among the population.
Example 1: Agribots for Area-Specific Precision Farming
Farmers are striving to increase efficiency and to save costs through the intelligent networking of people, animals, and machines. Agricultural technology plays a crucial role in this by increasing quality and efficiency, and conserving resources. The digitalization of agriculture is being driven by the increased use of agribots for precision farming and soil-monitored irrigation.
The combination of soil and weather monitoring with automated irrigation systems enables efficient water management with significant savings of 30 to 50 percent. Agribots, such as unmanned tractors, robots, weed killers, and drones significantly reduce costs and labor. Weed killers use cameras to detect weeds and apply targeted herbicides or electric shocks, while drones collect data on plants and animals.
Example 1: Agribots for Area-Specific Precision Farming
Farmers are striving to increase efficiency and to save costs through the intelligent networking of people, animals, and machines. Agricultural technology plays a crucial role in this by increasing quality and efficiency, and conserving resources. The digitalization of agriculture is being driven by the increased use of agribots for precision farming and soil-monitored irrigation.
The combination of soil and weather monitoring with automated irrigation systems enables efficient water management with significant savings of 30 to 50 percent. Agribots, such as unmanned tractors, robots, weed killers, and drones significantly reduce costs and labor. Weed killers use cameras to detect weeds and apply targeted herbicides or electric shocks, while drones collect data on plants and animals.
Spectral Analysis and Plant Metabolism
The Fraunhofer Institute for Factory Operation and Automation IFF is researching modern sensor solutions for agriculture. The goal is to increase ecological sustainability and efficiency. The focus here, is on the ecosystem.
As a result, the researchers present the technology “HawkSpex”, an adaptive
intelligent sensor system. It captures the condition of plants without laboratory analysis. The technology was tested in viticulture in the “BigGrape” project. At the heart of the solution are soft sensors, also known as virtual sensors. These are created by combining hardware sensors and software evaluations with machine learning methods. They not only detect visible light, but also infrared and ultraviolet radiation. Intelligent spectral analyses record the health status of the plants.
The result is a “spectral fingerprint”. From this, a mathematical algorithm calculates the material composition of the plants. Depending on their state of health, they produce different substances that become visible with the help of spectral analysis. Other parameters such as water shortage or pest infestation are also captured by the non-invasive measurement of plant metabolism.
Spectral Analysis and Plant Metabolism
The Fraunhofer Institute for Factory Operation and Automation IFF is researching modern sensor solutions for agriculture. The goal is to increase ecological sustainability and efficiency. The focus here, is on the ecosystem.
As a result, the researchers present the technology “HawkSpex”, an adaptive
intelligent sensor system. It captures the condition of plants without laboratory analysis. The technology was tested in viticulture in the “BigGrape” project. At the heart of the solution are soft sensors, also known as virtual sensors. These are created by combining hardware sensors and software evaluations with machine learning methods. They not only detect visible light, but also infrared and ultraviolet radiation. Intelligent spectral analyses record the health status of the plants.
The result is a “spectral fingerprint”. From this, a mathematical algorithm calculates the material composition of the plants. Depending on their state of health, they produce different substances that become visible with the help of spectral analysis. Other parameters such as water shortage or pest infestation are also captured by the non-invasive measurement of plant metabolism.
Digital Herd Management with Sensors and AI
In the “DigiMilch” project of the Bavarian State Research Center for Agriculture, sensors are used to record the health status of livestock. The productivity of livestock, and thus, economic success, depend on the health of the animals. By monitoring livestock in real time, sick animals can be detected at an early stage.
Farm animals are equipped with sensor systems. These are usually attached to the animal’s ear, neck or foot. Parameters such as the number of steps, lying time, standing time, chewing time, eating time, body temperature, and number of drinking cycles are measured. The collected data is transferred to a smartphone or computer in real time.
AI assistance systems evaluate the data. If the system detects irregularities such as longer lying times, reduced movement, or a drop in body temperature, an alarm is triggered. Farmers can store all the recorded data either locally on farm computers or in inter-farm networked systems. Inter-farm networked systems facilitate access to the data by authorized third parties such as external breeding organizations or consultants.
Artificial intelligence plays an important role in evaluating the growing data networks in order to draw conclusions about changes in all animals. Health problems such as feeding problems or reduced fertility can be detected at an early stage with the help of AI.
Digital Herd Management with Sensors and AI
In the “DigiMilch” project of the Bavarian State Research Center for Agriculture, sensors are used to record the health status of livestock. The productivity of livestock, and thus, economic success, depend on the health of the animals. By monitoring livestock in real time, sick animals can be detected at an early stage.
Farm animals are equipped with sensor systems. These are usually attached to the animal’s ear, neck or foot. Parameters such as the number of steps, lying time, standing time, chewing time, eating time, body temperature, and number of drinking cycles are measured. The collected data is transferred to a smartphone or computer in real time.
AI assistance systems evaluate the data. If the system detects irregularities such as longer lying times, reduced movement, or a drop in body temperature, an alarm is triggered. Farmers can store all the recorded data either locally on farm computers or in inter-farm networked systems. Inter-farm networked systems facilitate access to the data by authorized third parties such as external breeding organizations or consultants.
Artificial intelligence plays an important role in evaluating the growing data networks in order to draw conclusions about changes in all animals. Health problems such as feeding problems or reduced fertility can be detected at an early stage with the help of AI.
Insect Monitoring with RFID
In the Sens4Bee joint research project of the Berlin-based Fraunhofer Institute for Reliability and Microintegration (IZM), bees are equipped with a tiny data backpack containing a 2 x 2 millimeter microbattery, an RFID tag, a data logger, and integrated sensors. The backpack weighs a total of 10 milligrams and is attached to the bee with a bio-compatible adhesive. The battery is charged via a solar cell and energy generation.
The aim of the project is to collect data on how climate change and intensive agriculture affect bees, and which factors contribute to bee mortality.
Insect Monitoring with RFID
In the Sens4Bee joint research project of the Berlin-based Fraunhofer Institute for Reliability and Microintegration (IZM), bees are equipped with a tiny data backpack containing a 2 x 2 millimeter microbattery, an RFID tag, a data logger, and integrated sensors. The backpack weighs a total of 10 milligrams and is attached to the bee with a bio-compatible adhesive. The battery is charged via a solar cell and energy generation.
The aim of the project is to collect data on how climate change and intensive agriculture affect bees, and which factors contribute to bee mortality.
“In the Sens4Bee project, bees are equipped with a data backpack containing an RFID tag, sensors, and our battery. During their flight, the bees generate data that allows us to draw conclusions about the effects of climate change and intensive beekeeping and helps us to understand and ultimately prevent bee mortality.”
Dr. Robert Hahn
Group Leader Microenergy Systems, Fraunhofer IZM
More Articles from the Agricultural Sector
Evaluation of IoT in Agriculture
Although the industrialization of agriculture continues to progress and the agricultural areas of individual farms are becoming ever larger, innovative digitalization solutions are only being integrated selectively. Agriculture is currently facing challenges in other areas. This includes, in particular, the uncertainty of crop yields, the explosion in costs, and increasing competition from industrially produced substitute products. Farmers are currently struggling with price increases, changes in the subsidy sector, succession issues and, last but not least, network expansion.
Solutions based on telematics, smart farming, metaverse, robotics, artificial intelligence or, RFID in agriculture are exceptions. Numerous fields of application, from termperature monitoring in food logistics, to container management, the maintenance and servicing of machines, and AI solutions to reduce harvest risks, are among the innovative goals for research and development.
Examples show that wireless IoT technologies are already being implemented in certain areas. These solutions are most frequently found in the logistics sector, in mechanical engineering, and in food production. Sensor-based solutions in crop cultivation or animal husbandry are promising, but also complex to install in terms of hardware and software. Overall, agriculture is an industry in which many wireless IoT solutions are possible.
Smart Farming with 5G, AI, and Big Data?
According to research, wireless sensor networks and IoT sensors are primarily being used to measure environmental parameters such as weather data (temperature, humidity, probability of rain), and soil dryness. There are also sensors that monitor the health data of animals. The latest research approaches focus on embedded systems that measure parameters such as enzymes or nucleic acids.
Data collected by these sensors is forwarded to so-called nodes or sensor nodes after the measurement. The transmission takes place via Wireless Wide Area Network (WWAN), WLAN, Bluetooth LE, Zigbee or LoRaWAN. Researchers see LPWAN technology and 5G as drivers of future IoT in agriculture.
Partners Spezialized in Agricultural Solutions
Challenges for Agriculture in 2024
Analysts predict another difficult year for agriculture in 2024. The pressure to produce food more efficiently is increasing, while uncertainty about sufficient rainfall during the growing season remains. One of the biggest challenges in the coming decades is the growth of the world’s population. Today, 8 billion people live on the planet. The United Nations forecasts 8.5 billion by 2030 and 9.7 billion by 2050, and although population growth has slowed recently, an increase in agricultural productivity is necessary to ensure food security for all.
Record temperatures have been measured every year since 2014. 2022 was one of the warmest years since weather records began, with the global average temperature at 1.15 degrees above pre-industrial levels. Global warming is extending the growing season, which seems positive. However, the likelihood of heatwaves and droughts is also increasing. In 2022, spring was too dry in large parts of Europe, which continued in summer.
In 2023, farmers were faced with rising production costs and falling prices. Prices for crop protection products rose by 24 percent and those for fungicides by just under 10 percent. The prices for oil (up to 9 percent) and gas (up to 47 percent) have also risen significantly. Speculation in agricultural commodities and the production of agrofuels contribute to the price fluctuations. Rising prices lead to a drastic drop in demand, especially among dairy farmers.
In modern agriculture, new technologies are transforming traditional practices. While concepts such as Farming Metaverse, Computer Vision, Digital Twin, and Machine Learning Agriculture are promising, their integration into agricultural practice is still limited. Challenges such as high costs, technical complexity, and the need for customization hinder widespread adoption. Despite these obstacles, the agricultural community recognizes the transformative potential of these technologies. With further research, development, and collaboration, the path to their wider adoption is becoming clearer and promises a future where farms operate more efficiently, accurately, and sustainably.
Outlook and Vision
Smart farming is revolutionizing agriculture by using advanced technologies to improve the efficiency, productivity, and sustainability of farms. A key component in this area is recycling in agriculture, which aims to use resources efficiently and to reduce waste. By using RFID technology in agriculture, farms can better manage and track their resources, from seeds to harvesting machines, and thus, also control recycling processes.
In the future, special agricultural software and telematics systems will be used as part of smart farming, helping to precisely capture and analyze data in order to optimally manage soil conditions, plant growth, and livestock. These technologies enable effective farm tracking, in which the movements and health of the animals, as well as the condition of the soil, vegetation, and weather data can be monitored in real time.
The integration of smart farming into the concept of the “smart city” is new and expands the potential of urban agriculture by enabling food production to be integrated efficiently and sustainably into urban structures. Agriculture thus becomes part of the urban supply chain, which shortens delivery routes and increases the freshness of products.
Overall, smart farming builds a bridge between traditional agriculture and modern technological solutions, improves the supply chain digitalization in agriculture, and promotes sustainable practices that are crucial to meet the challenges of the 21st century.
Industrial Trends for Agriculture
The importance of industrial trends for agriculture has increased enormously in recent years and is shaping the way farms operate today. One key trend is big data farming, which makes it possible to collect and analyze huge amounts of agricultural data. By using this data, farmers can make informed decisions, maximize crop yields and use resources more efficiently. This leads to more sustainable and profitable farming.
Another major trend is the Farming Metaverse, a virtual environment that enables farmers to digitally simulate and optimize their farms. Using Agriculture Digital Twin technology, farmers can create digital replicas of their fields and equipment. These digital twins provide valuable insights and allow different scenarios to be tested before they are implemented in the real world. This improves planning and reduces the risk of errors.
Big data in agribusiness also has a major impact on agriculture. By analyzing market data, weather forecasts, and soil information, farms can adapt their strategies and remain competitive. Agriculture IoT solutions, i.e. networked devices and sensors, enable precise monitoring and control of agricultural processes. These technologies help to optimize water consumption, monitor soil health, and minimize the use of fertilizers and pesticides.
5G Smart Farming is revolutionizing agriculture by providing high-speed internet connections that improve communication between different IoT devices. This enables real-time monitoring and control of agricultural activities and promotes automation and efficiency.
Machine learning in agriculture is another important trend. By using algorithms to analyze field data, predictions can be made about crop yields, pest infestation, and soil fertility. This helps farmers to act proactively and continuously improve their cultivation methods.
E-learning in agriculture also plays an important role. It provides farmers with access to educational resources and training to help them understand and apply the latest technologies and best practices. This promotes the dissemination of knowledge and contributes to the modernization of agriculture.
Finally, computer vision farming is revolutionizing the way farmers monitor their fields. By using cameras and image processing techniques, weeds, pests, and plant diseases can be detected at an early stage. These technologies enable precise and targeted treatment, resulting in healthier plants and higher yields.