Smart Farming
Digitale Technologien für die Landwirtschaft von morgen.
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Automatisierung
Ausgewählte Forschungsprojekte zum Thema
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I4S aims at developing a sensor-based system on bases of which in particular recommendations for a site-specific fertilization management should be provided and which should contribute to improving soil functions and to …
Start:
End:
01.11.2018
28.02.2022
Funding authority:
Bundesministerium für Bildung und Forschung (BMBF)
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SMART4ALL builds capacity amongst European stakeholders via the development of selfsustained, cross-border experiments that transfer knowledge and technology between academia and industry. It targets CLEC CPS and the IoT…
Start:
End:
01.01.2020
31.12.2023
Funding authority:
Europäische Union (EU)
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The vision underlying DAKIS (Digital Agricultural Knowledge and Information System) is that spatially and functionally diversified production systems are able to harmonize contradictory land use goals. The project realiz…
Start:
End:
01.04.2019
31.03.2024
Funding authority:
Bundesministerium für Bildung und Forschung (BMBF)
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The aim of the collaborative project is to develop a modularized mobile system, which will enable an initial spatio-temporal high-resolution population monitoring (4D) of insect populations in orchards, in order to imple…
Start:
End:
01.01.2020
31.12.2022
Funding authority:
Bundesministerium für Ernährung und Landwirtschaft (BMEL)
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The objective of the weed-AI-seek project is to develop an intelligent real-time monitoring and mapping system for the detection of weed distribution in cereal stands. For this purpose, high-resolution aerial image data …
Start:
End:
28.05.2021
27.05.2024
Funding authority:
Bundesministerium für Ernährung und Landwirtschaft (BMEL)
Weitere Projekte zum Thema suchen ...
Ausgewählte Publikationen
- Shamshiri, R.; Kalantari, F.; Ting, K.; Thorp, K.; Hameed, I.; Weltzien, C.; Ahmad, D.; Shad, Z. (2018): Advances in greenhouse automation and controlled environment agriculture: A transition to plant factories and urban farming. International Journal of Agricultural and Biological Engineering. (1): p. 1-22. Online: https://ijabe.org/index.php/ijabe/article/view/3210
- Shamshiri, R.; Weltzien, C.; Hameed, I.; Yule, I.; Grift, T.; Balasundram, S.; Pitonakova, L.; Ahmad, D.; Chowdhary, G. (2018): Research and development in agricultural robotics: A perspective of digital farming. International Journal of Agricultural and Biological Engineering. (4): p. 1-14. Online: https://www.ijabe.org/index.php/ijabe/article/view/4278/1737
- Techen, A.; Helming, K.; Brüggemann, N.; Veldkamp, E.; Reinhold-Hurek, B.; Lorenz, M.; Bartke, S.; Heinrich, U.; Amelung, W.; Augustin, K.; Boy, J.; Corre, M.; Duttmann, R.; Gebbers, R.; Gentsch, N.; Grosch, R.; Guggenberger, G.; Kern, J.; Kiese, R.; Kuhwald, M.; Leinweber, P.; Schloter, M.; Wiesmeier, M.; Winkelmann, T.; Vogel, H. (2020): Soil research challenges in response to emerging agricultural soil management practices. Advances in Agronomy. (161): p. 179-240. Online: https://www.sciencedirect.com/science/article/pii/S0065211320300146?via%3Dihub
- Vogel, S.; Gebbers, R.; Oertel, M.; Kramer, E. (2019): Evaluating soil-borne causes of biomass variability in grassland by remote and proximal sensing. Sensors. (20): p. 4593. Online: https://doi.org/10.3390/s19204593
Weitere Publikationen zum Thema suchen ...
