Trends in digital systems and information technology

Digitalization is permeating every aspect of our professional and personal lives to an extent never seen before. This development is also evident in agriculture, especially in agricultural machinery.

As a result, almost no new machine, system, or product appears on the market without more or less complex electronics and software. The more expensive a product, the more important professional service and maintenance become.

Consequently, higher-performance machines are naturally connected to the internet. However, the trend toward ever-increasing automation requires increasingly intelligent systems, such as the use of complex sensor technology, control and regulation technology, and artificial intelligence.

Intelligent systems to increase automation

However, this trend is no coincidence; it is essentially due to the following factors:

• The demand for quality work in the various processes involved in agricultural production is constantly increasing. Precision in soil cultivation, seeding technology, crop protection, fertilization, and harvesting technology requires sophisticated process control and monitoring, as well as the corresponding sensor and actuator technology.

• Machine complexity is constantly increasing. On the other hand, there is a shortage of suitably qualified operational personnel. Such intelligent and complex systems require an operational concept that is as simple as possible.

• There is considerable pressure to further increase work efficiency. Resources must be conserved and working hours reduced. Therefore, machine power must be further increased. Machine settings must therefore be adjusted as precisely as possible to environmental conditions. This also requires appropriate sensor technology.

• Problems, errors, and component or system failures consume significant time and money. Therefore, problems must be identified early, which requires the use of sensor technology, which can be very complex in some cases.

• Due to climate change, with periods of drought on the one hand and heavy rainfall on the other, it becomes increasingly necessary to recognize unexpected situations and respond to them flexibly.

• Time and cost pressures ultimately drive machines and systems to become increasingly automated and, ultimately, to operate autonomously. The system must monitor itself, its environment, and the work process, and be incorporated into a management system.

However, this is only possible thanks to the rapid development of innovative new technologies. Digitalization, and artificial intelligence in particular, currently plays an important role. As long as the appropriate data is available, AI methods can be used to model a wide variety of processes. This makes it possible, for example, to obtain information from image data for process control.

Models can be trained based on this. High-quality models enable predictions, thus facilitating automated decision-making processes. This requires comprehensive sensor systems and machine learning methods. Thanks to accessible communication technologies, process data is often delivered directly to the manufacturer's cloud, where it can be conveniently evaluated and processed.

Many new developments are evident in this area, which are described in more detail below.

Innovative developments

Developments in the area of ​​digital systems and IT have been divided into four different categories, some of which overlap:

• Sensor technology and forecasting systems

• Computer vision

• Supply Chain

• Hardware and software components

Sensor technology and forecasting systems

Sensors are used to record individual parameters and provide data. To accurately assess situations and base decisions on them, it's often necessary to implement pre-trained models using AI methods. Vibration monitoring is a typical example.

A Agrosentinels Kft. offers a vibration sensor of the same name in combination with a diagnostic system that allows real-time fault monitoring and early detection of damage to agricultural machinery components.

the italian company COMET SpA presents Campus, a diagnostic system for pumps in crop protection equipment based on various sensors. EMILIANA SERBATOI SrL offers Emil Level, a level sensor designed primarily for use in mobile tanks.

Another very interesting product is the Intuitu Smart Pressure Assistant from Nokian Heavy Tires Ltd. Just like a tire pressure monitoring system, the tire pressure sensor is integrated directly into the tire and transmits pressure, temperature, and weight data to a smartphone via the cloud. This allows for convenient adjustment of the correct tire pressure. TECALEMIT Flow is a flow meter for tank systems that is also connected to a data cloud.

Tailored irrigation is becoming increasingly important. The prerequisite for this is knowledge of the water available to plants in the soil. To achieve this, Drought Analytics GmbH, a spin-off of the Jülich Research Center, has developed Dürrepilot, which provides a powerful irrigation management system based on TDR sensors in the ground, plant models and daily weather forecasts.

The Austrian company Bauer, an irrigation specialist, developed Cosmofield. It uses the principle of cosmic neutron detection to measure soil moisture. One sensor covers 5 to 10 hectares of arable land, eliminating the need for a large number of individual soil sensors.

In the field of pest detection, EFOS doo introduces the AURA 2 SC, a solar-powered insect trap that uses UV light instead of pheromones and features AI-based assessment. The same company also developed the BARKB SC, a solar-powered beetle trap with automated assessment.

Computer vision

The development of increasingly affordable camera systems and, above all, the possibilities of image analysis through machine learning have led to a number of new developments. In particular, the evaluation of drone imagery is becoming increasingly diverse.

A Proofminder Services uses high-resolution drone and camera imagery in AI Agronomist for weed detection, yield prediction, crop counting, weather and wildlife damage assessment, and accurate spray maps, supporting over 30 use cases.

ZONEYE, from Skymaps sro, also uses a cloud-based AI algorithm to detect over 30 plant species from drone footage. Kiel University of Applied Sciences developed Dynamic Field Scout, which uses drone orthophotos to determine the current and exact contours of the field and also detect obstacles in the process. Photoheyler GmbH offers the Custom AI training platform to train AI algorithms with the user's own images.

A Brigade Electronics offers a new front camera monitoring system with AI-based person and traffic detection, including alert messages. The front camera has already been tested by DLG.

EasyMatch, from Amazonen Werke GmbH, allows automated adjustment of the fertilizer spreader, identifying the commercial fertilizer to be applied through image analysis. Hagedorn Software Engineering GmbH is launching VISION, an AI-based 3D camera system that can be used to monitor the performance of implements. For example, blockages in a cultivator can be automatically detected.

Vision Pro from FieldBee, on the other hand, is a retrofit solution for a steering system, but also includes an RGB and NIR camera to calculate a vegetation index (EVI) in real time. With WIN – Weeder Intelligent Network, Rau Serta Hydraulik GmbH offers a camera-based row recognition system for hoe control and track guidance.

A Claas developed AI-powered spare part recognition using image analysis of a photograph to quickly find the correct spare part.

Supply Chain

The more expensive and complex a system becomes, the more important machine management becomes. High machine utilization, monitoring, and optimized functionality are prerequisites for efficient operation.

A Lemken has already presented innovative developments in the past with iQblue. The iQblue tool monitoring system for assessing cultivator blade condition, introduced (and awarded) two years ago, has been expanded to become the iQblue Smart Implement. In addition to roller speed, crop flow is also monitored to detect blockages. iQblue Machine Connect allows combinations of devices with and without their own ISOBUS functionality to be networked into a single unit.

A Claas, on the other hand, has developed an AI-powered assistance system for machine operation and maintenance. A chatbot with an analytics module assists with specific questions and supports the planning of maintenance and repair measures at the authorized workshop. The Claas Green Yield Score enables the automated collection and allocation of emissions data throughout agricultural production chains. This involves allocating fuel consumption to the respective process stages.

With Carrier Connected Services, Case IH offers a total of four digital services to help drivers optimize the use of their machines, avoiding errors and increasing productivity. Operator Insight analyzes machine data in real time and provides immediate feedback to the driver. The Operational Report analyzes consumption, CO2 emissions, and performance, links the data to expert knowledge, identifies operational errors, and displays consumption and emissions trends, including specific suggestions for improvement. The Operational Dashboard offers dealers a powerful tool for proactive maintenance planning and service improvement. Operator Advisor generates individual driving feedback based on machine data.

A FarmBlick GmbH developed SRC Smart Relay Cropping, a tool for automatic track planning, field optimization and data transfer directly to the steering system.

With the TCU Traction Control Unit from AgXeed bvCentrally planned tasks can be performed with an existing multi-brand fleet (tractor, self-propelled machine, robot, etc.). Depending on the technology level, the scope of the order can range from track lines to complete routing, including implement configurations.

A Maschinenfabrik Bernhard Krone developed SPARTA, a system for the standardized description of the spatiotemporal behavior (trajectories) of machine movements. The goal is interoperability between combinations of machines from different manufacturers.

A Syngenta Agro GmbH is launching two new systems: Cropwise Operations AI Machine Pool, a machine rental platform that suggests optimal equipment combinations to farmers through real-time analysis of planned fieldwork and machine utilization. Machine Manager allows the creation of work orders taking into account field terrain, soil type and composition, weather conditions, and crop growth stages. An integrated telematics module enables machine allocation, quality control, and real-time monitoring.

A AGMO Inc. offers SeamOS, an "ecosystem as a service" platform. The open operating system allows the development of applications and plug-ins, for example, for ISOBUS applications.

With Panorama Passmaster, PTx provides real-time visualization of machine data, including data exchange between machines in the tractor cab, thus facilitating the coordination of work between multiple machines and operators by combining application maps.

Hardware and software components

New hardware and software components form the basis for more complex systems and a greater degree of automation.

A Motion Center developed a new display and controller called the CrossCore A100. The WEED-IT DASH from Rometron BB, on the other hand, is part of a localized spraying system consisting of a touchscreen, controller, and communication module. Neousys Technology GmbH offers the Fanless Flattop, a dustproof control unit with six camera inputs for AI applications. The STEERMASTER from marinelli is a system for sensor integration, remote control and data acquisition for autonomous driving.

The NX Next Motion Arnold NextG GmbH is extremely interesting. It's a complete drive-by-wire system that replaces mechanical steering, braking, and drive connections with electronic ones and is approved for road use. The same company's DUXALPHA retrofit solution is a 3D guidance system for off-road terrain. Lanes are planned according to terrain slope and working width.

The logiBUS2026 of HR Agrartechnik GmbH is an excellent example. This is the next version of an intuitive graphical development environment for ISOBUS applications. ISO Cloud Control from Zunhammer Also interesting: here, the ISOBUS Task Controller is directly connected to the cloud. A new application card is therefore immediately synchronized with the vehicle.

The Smartstick of Hagedorn Software GmbH replaces the flash drive for transferring orders, driving routes, and application maps with an app on the user's smartphone. The terminal recognizes it as a flash drive. AgGateway introduces a new version of ADAPT, a data model for a common, portable, and interoperable file layout.

With Mela, the IAV GmbH offers a system that can be used to analyze large videos, measurement data, or text. VLLM—a tool already widely used in the automotive industry—enables the generation of critical driving scenarios.

Conclusion and perspectives

This year's Agritechnica will also showcase a wide range of new developments in digital systems and IT. The possibilities offered by artificial intelligence, and machine learning in particular, are being explored in a variety of applications.

In image processing, in particular, this can be used to generate information previously only available to humans. Sophisticated components within complex systems require the development of new management systems so that machines can be used efficiently. Decisions are increasingly being transferred to the system.

Therefore, it is expected that more and more autonomous systems will be introduced in the future, but their beneficial application also needs to be proven.

By Heinrich Prankl, Wieselburg (Austria)