It is only through digital change, networking and intelligent equipment that further optimization potential will be found along the entire agricultural value chain. Increasingly, agricultural machines are equipped with intelligent technologies. These are not limited to individual software and hardware products; today, the entire digital infrastructure, such as networks, data on universal data platforms (including from cloud applications and apps on smartphones) are also accessible to our farm machinery. This ongoing process of change, known as digital transformation, is unstoppable in all areas of modern life.
Platform for digital solutions
The Systems & Components special feature at Agritechnica 2017, which takes place at Hanover’s exhibition grounds from 12 to 18 November (preview days on 12 and 13 November), will showcase the systems, modules, components and accessories that are used to manufacture today’s farm machinery. As part of the world's largest trade fair for agricultural technology, the special feature has the motto "Stay connected!" this year, and will also take up the latest trends such as "Digital Transformation”, “Big Data” and the “Internet of Things". Systems & Components will enable a challenging exchange of knowledge between exhibitors and visitors. "Connectivity" is not only the prerequisite for fine-tuning modern, highly complex systems using mechanical, hydraulic and electronic components, but also between man and machine.
Innovations and solutions from the fields of engines, hydraulics, axles, drive technology, cabins, electronics, spare and wearing parts will all be presented in the special feature, and with experts from about 700 exhibitors present, this presents the ideal platform for exchanging information about trends and solutions from the unstoppable digitization underway in the field of agricultural technology.
Internet of Things & Big Data
The Internet of Things (IoT) is a vision for the global infrastructure of the information society. It is intended to network physical and virtual objects, and to allow them to work together by using information and communication techniques. Single, intelligent machines in the field can be turned into so-called co-operative machines by combining several of them together and with the data that manages their operating processes being interchanged. The level of "authority" given to each tractor determines the level of influence it can have on the mutual control system. IoT is already active in the field of agricultural technology through the development of new sensor technology, software products and intelligent, communicating machines.
Big Data, which is also sometimes called mass data, is often also seen as a collective term for digital technologies. The data obtained from farms is collected, analyzed and structured. Real-time flows of data can directly influence the efficiency of agricultural operation, and the possibilities of integrating big data must be considered in the development of machinery for the agricultural machinery.
The potential of digital transformation in agricultural technology must be recognized and used throughout the workflow in a future-proof manner. Intelligent, sustainable solutions are in demand from today’s agri-businesses, and some of the examples of the new technologies being developed that can be seen in the Systems & Control special feature follow.
The CAB Concept Cluster, made up of experienced OEM suppliers and industry organizations – Aurora, Robert Bosch GmbH, Fritzmeier Group, Grammer, Hella, Hydac, Mekra Lang, S.M.A., Lumod, TU Dresden, AEF (Agricultural Industry Electronics Foundation), DEULA (Association of German Educational Institutes for Agricultural technology) – and the DLG (German Agricultural Society), will use Systems & Components to showcase its project that focuses on bundling near-serial-production innovations in joint projects and identifying the potential for new efficient system integrations.
The organization’s Smart CAB agricultural machine cabin project enables maximum x2x (something-2-something) usability in the communication between driver and machine, and machine and cloud or other components thanks to the extremely powerful CAN (controller area network) structure. As an open system, the IoT-enabled Smart CAB offers unlimited networking and thus the highest degree of future security. The integrated connectivity unit (CCU) sends vehicle data to a back-end and accesses the Bosch Feature Store. This allows new functions and features for the machine to be loaded in series. Manufacturers and farmers can share broadly usable data and use it for new business models. Digital products from other manufacturers can also be integrated flexibly.
Ground cover analysis via image processing
Josephinum Research is working on a method to automatically determine the degree of soil coverage by a crop from images in its "SoilCover" research project. The system uses an algorithm is based on an automatic pixel-wise classification of ground images of the earth into either crop residues, living plant material and stones. Images are taken via a smartphone or conventional camera from a height of one meter. If several images are recorded from a field, the entire ground coverage can be calculated.
The evaluation is carried out by means of mobile data acquisition, and via a client/server architecture. The result is immediately available to the user, for example via a smartphone app. The results obtained are intended to represent a basis for further commercial and scientific utilization in agricultural technology as it will allow a more efficient way of working.
Agrifusion research project
The Weihenstephan-Triesdorf University of Applied Sciences is investigating new procedures for generating profit potential maps in its Agrifusion project being carried out in conjunction with Germany’s Federal Ministry of Agriculture and Food, the German Geological Research Center, GeoInformationsDienst GmbH and Fritzmeier Environmental Engineering. Data from individual sensors (including from satellites and drones, yield data, elevation data, soil conductivity and nitrogen absorption) are collected in a networked manner, merged centrally on a server and processed. The aim is to determine the yield potential of soils more precisely, and with these findings the deployment of resources and use of agricultural technology can be optimized. This will generate positive effects for the environment and the income situation of the farmers.