5G Smart Country



Prof. Dr.-Ing. Jorge Marx Gómez


Secretary Julia Franke

+49 (0) 441 / 798 - 44 78

+49 (0) 441 / 798 - 44 72 

A4 - 3rd floor

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5G Smart Country

5G Smart Country

Increasing global population (estimated to be over 9 billion by 2050), depleting natural resources, and harshening climate conditions make coping with these challenges and a significant increase in agricultural productivity an imperative. Projections indicate that globally agricultural production will need to expand by more than 50% by 2050 to meet increased demand, and most of this will need to come from increased agricultural productivity as deforestation to create more agricultural space can only exacerbate the problem particularly by contributing to global warming and consequently, even further stressing the agriculture. We, therefore, need to grow more on existing farmland, without increasing negative impacts on the available natural resources and environment.

Modern information and communication technologies (ICT) are already contributing to various sectors of economy, including agriculture. Smart agriculture refers to the usage of ICT, like Internet-connected sensors (Internet of Things, IoT), robots, automatic agricultural machines, precise deployment of resources like fertilizers on the farm and in the forest. The ultimate goal is increasing the quality and quantity of the crops while minimizing the resources and human labor used as well as preserving environment.

However, the existing ICT infrastructure is not efficient enough to unfold the full potential of automation and precision in smart farming and forestry. 5G cellular technology with its prime features like lower latency, higher capacity, and increased bandwidth compared to 4G is capable of near real-time applications, for instance, the use of video-equipped drones to monitor crop and timber conditions, livestock, and wildlife.  

The living lab project "5G Smart Country" aims at developing and testing 5G applications in smart farming and forestry in the pioneering regions of Wolfenbüttel and Helmstedt in Niedersachsen. The project is conceived as a research alliance with partners from various research institutes, and agricultural and biosystems engineering firms. The project is funded by the German Federal Ministry of Transport and Digital Infrastructure (BMVI) under its program “5G Initiative for Germany”.

Key aims/Technical overview of the project: Data from forest and farm will be collected using IoT sensors and drones with special remote sensing cameras. Data analytical algorithms will serve to understand the data and make the right/required decisions, for instance, to differentiate between useful plants and weed so that fertilizer could be used precisely (where and how much: pointed fertilizing/microdosing) and environment-friendly weeding robots could be deployed instead of reverting to environment-damaging chemical-based methods/herbicides; keep track of wildlife; do real-time spectroscopic measurements to assess the quality of the harvest (smart harvesting); gather reliable forest inventory and enable controlled and efficient timber harvesting.

Participating Partners

  • Deutsches Zentrum für Luft- und Raumfahrt e.V., 
  • Julius-Kühn-Institut für Kulturpflanzen (Institut für Anwendungstechnik im Pflanzenschutz),
  • Landwirtschaftskammer Niedersachsen, 
  • Ostfalia Hochschule,   
  • Rauch Landmaschinenfabrik GmbH, 
  • Strube D&S GmbH,
  • Technische Universität Braunschweig (Institut für mobile Maschinen und Nutzfahrzeuge, IMN), 
  • Thünen-Institut für Waldökosysteme,
  • Universität Oldenburg (Chair of Very Large Business Applications, VLBA),
  • Wahlers Forsttechnik GmbH & Co.KG.

Associated partners

  • Domäne Schickelsheim
  • Niedersächsische Landesforsten
  • Rittergut Lucklum
  • Stiftung Zukunft Wald 

The overall coordination of the collaborative research project will be conducted by a steering committee formed by the two counties involved in this pilot project, Wolfenbüttel and Helmstedt.
The University of Oldenburg (VLBA) has a strong representation in this research project. The main focus lies on developing algorithms for data analysis and decision-making using data science and artificial intelligence methods.

Project start


Project end



(Changed: 19 Dec 2022)  | 
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