LAND.TECHNIK 2024

doi:10.51202/9783181024447

LAND.TECHNIK 2024

Reihe: VDI-Berichte

Band 2444 1. Auflage 2024

Kein Zugriff

doi.org/10.51202/9783181024447
ISBN print: 978-3-18-092444-1
ISBN online: 978-3-18-102444-7
VDI Verlag, Düsseldorf VDI Verlag, Düsseldorf

Im Shop erwerben

Zusammenfassung

Content Vehicle Guidance Track Planning – an implements point of view 1 Guiding principles and challenges in the context of environment perception and geofencing in the agricultural application domain 7 Automatic track guidance in high-standing maize crops 15 Standardization AEF – Digital Camera Systems – A new project team working on an AEF Functionality for High Speed ISOBUS 21 Introducing the AEF Autonomy in Ag project 29 Integrating High-Speed Data Communication via Automotive Ethernet with a Service-Oriented Architecture Established using SOME/IP in Agricultural Machinery 37 ISOBUS Migration From CAN to Ethernet – Doing it Right From the Beginning 43 Innovations through AI Technologies Green revolution – AI for precise weed and pest control 49 Accelerating the AI lifecycle with the AgriGaia-Platform Presentation of a modular platform concept used to support AI developers, based on open-source software 63 Edge-Cloud Intelligence and AI for Large-scale Agricultural Production Systems 69 Data Integration in Agricultural Engineering Facilitating seamless collaboration: Secure decentralized group management in interoperable wirele...

Schlagworte

Fahrzeug Lenkung KI Technologien Datenintegration Landtechnik Energie Lösungen ergonomische Einschätzung Mähdrescher digitaler Zwilling Automation Farming digitale Innovation Kultivierung nachhaltige Energie vehicle guidance AI technologies data integration agricultaral engineering energy solutions ergonomics assessment combine harvester digital twins automation farming digital innovation cultivation sustainable energy

Kapitel Ausklappen | EinklappenAutorenSeiten
I–XII Titelei/Inhaltsverzeichnis I–XII
1–20 Vehicle Guidance 1–20
- 1–6 Track Planning – an implements point of view M. Roeingh M. Roeingh 1–6
- 7–14 Guiding principles and challenges in the context of environment perception and geofencing in the agricultural application domain A. Tauber, S. Röttgermann, A. Grever A. Tauber, S. Röttgermann, A. Grever 7–14
- 15–20 Automatic track guidance in high-standing maize crops R. Konradt, A. Scholz, M. Laghbani, S. Schmidt R. Konradt, A. Scholz, M. Laghbani, S. Schmidt 15–20
21–48 Standardization 21–48
- 21–28 AEF – Digital Camera Systems – A new project team working on an AEF Functionality for High Speed ISOBUS N. Niebrügge, D. Schäfer N. Niebrügge, D. Schäfer 21–28
- 29–36 Introducing the AEF Autonomy in Ag project A. Grever, R. Abel A. Grever, R. Abel 29–36
- 37–42 Integrating High-Speed Data Communication via Automotive Ethernet with a Service-Oriented Architecture Established using SOME/IP in Agricultural Machinery A. Lohmann A. Lohmann 37–42
- 43–48 ISOBUS Migration From CAN to Ethernet – Doing it Right From the Beginning P. Fellmeth, M. Schlodder P. Fellmeth, M. Schlodder 43–48
49–74 Innovations through AI Technologies 49–74
- 49–62 Green revolution – AI for precise weed and pest control K. A. Rösler, K. Szelechowicz K. A. Rösler, K. Szelechowicz 49–62
- 63–68 Accelerating the AI lifecycle with the AgriGaia-Platform Presentation of a modular platform concept used to support AI developers, based on open-source software H. Tapken, T. Wamhof, H. Graf, A. Schliebitz, L. Hesse, M. Fruhner, J. Tüpker H. Tapken, T. Wamhof, H. Graf, A. Schliebitz, L. Hesse, M. Fruhner, J. Tüpker 63–68
- 69–74 Distributed Edge-Cloud Intelligence and AI for Large-scale Agricultural Production Systems A. R. M. Wagner, P. Pickel, A. Locatelli A. R. M. Wagner, P. Pickel, A. Locatelli 69–74
75–102 Data Integration in Agricultural Engineering 75–102
- 75–80 Facilitating seamless collaboration: Secure decentralized group management in interoperable wireless in-field communications D. Steinmetzer, M. Stute, J. Witte, T. Nothdurft D. Steinmetzer, M. Stute, J. Witte, T. Nothdurft 75–80
- 81–86 Current situation and challenges of automatization standards in farm machinery and FMIS from a dealer perspective Future development of agricultural machinery dealer business S. Wöbcke, T. Herlitzius S. Wöbcke, T. Herlitzius 81–86
- 87–96 Decentral and Central Technologies combined to one „DataXChange System“ J. Sonnen, O. Rahner J. Sonnen, O. Rahner 87–96
- 97–102 EU Data Act: Data governance as an enabler P. Altschuh, S. Held P. Altschuh, S. Held 97–102
103–126 Energy Solutions and Ergonomics Assessment 103–126
- 103–112 Fuel cell electric agricultural tractor FCTRAC: operation strategy, homologation, benchmarking, and field testing J. Konrad, C. Varlese, C. Junger, R. Krizan, P. Hofmann, C. Mayer J. Konrad, C. Varlese, C. Junger, R. Krizan, P. Hofmann, C. Mayer 103–112
- 113–118 Is fast charging relevant and beneficial for agricultural machinery? D. Mühlgrabner, R. Kruth, J. Roth, B. Langer D. Mühlgrabner, R. Kruth, J. Roth, B. Langer 113–118
- 119–126 Evaluation of adaptive operating concepts on agricultural tractors in a laboratory test rig to assess cognitive and physical ergonomics B.-G. Hülle, V. Ernst, J. Boysen, S. Böttinger, M. Racs B.-G. Hülle, V. Ernst, J. Boysen, S. Böttinger, M. Racs 119–126
127–146 Combine Harvester 127–146
- 127–132 Modelling two-dimensional Separation Approach for Rotor Units of Combine Harvesters Combining Böttingers Separation Model and Wackers Crop Flow Model to a two-dimensional Separation Model for Rotor Un... M. Barther M. Barther 127–132
- 133–138 Digital Twins in Agricultural Engineering Benefits in Developing New Combine Harvester Concepts B. Thy, H. Korte B. Thy, H. Korte 133–138
- 139–146 Study on the use of DEM for the threshing process C. Korn, F. Uhlig, K. Düring Jensen, A. Andersen C. Korn, F. Uhlig, K. Düring Jensen, A. Andersen 139–146
147–178 Networking and Automation 147–178
- 147–158 Radio technologies for infrastructureless M2M communication for Ag applications around the world H. Keränen, J. Witte, T. Nothdurft, J. Olague, K. Lautenschlaeger H. Keränen, J. Witte, T. Nothdurft, J. Olague, K. Lautenschlaeger 147–158
- 159–168 Field Trials and Evaluation Methods for Sensors used in Perception Systems for Autonomous Machinery with Respect to SOTIF J. C. Krause, N. Iqbal, M. Niemeyer, J. Hertzberg, S. Röttgermann, A. Tauber, J. Herbers, S. Menke, L. Plagge, B. Thy, H. Hollmeier, S. Stiene J. C. Krause, N. Iqbal, M. Niemeyer, J. Hertzberg, S. Röttgermann, A. Tauber, J. Herbers, S. Menke, L. Plagge, B. Thy, H. Hollmeier, S. Stiene 159–168
- 169–178 Operation and investigation of adaptive mesh networks to increase the connectivity of agricultural machinery J. Hagert, T. Füldner, B. Striller, T. Herlitzius, A. Hecker, B. Turkowski, G. Fettweis, J. Schwardt J. Hagert, T. Füldner, B. Striller, T. Herlitzius, A. Hecker, B. Turkowski, G. Fettweis, J. Schwardt 169–178
179–204 Process Automation 179–204
- 179–186 SpeeDiFlow – Non-invasive Measurement of Air Speed and Direction A robust Sensor for Particle-Laden Flows A. Günther, F. Uhlig, C. Korn, S. Müller, P. Mitlöhner, K. Kränzel A. Günther, F. Uhlig, C. Korn, S. Müller, P. Mitlöhner, K. Kränzel 179–186
- 187–194 Field evaluation insights of a novel optical sorting approach suitable for mobile operation on a potato harvester M. Brinkmann, J. Roß, W. Strothmann, T.-F. Minßen M. Brinkmann, J. Roß, W. Strothmann, T.-F. Minßen 187–194
- 195–204 Tillage Quality Measurement: Surface Roughness Analysis using Height Profiles M. Graf, M. Geimer M. Graf, M. Geimer 195–204
205–234 Parameter Measurement in Farming 205–234
- 205–214 Fusing SAR and Weather with Physics-Inspired ML for Improved Soil Moisture Estimation T. Das, B. Rodriguez, B. Mathai, J. Just T. Das, B. Rodriguez, B. Mathai, J. Just 205–214
- 215–222 Systematic Data Selection for Enhanced Nutrient Prediction and Monitoring in Manure Using NIR L. Friedrich, K.-L. Krieger, J. van den Broek L. Friedrich, K.-L. Krieger, J. van den Broek 215–222
- 223–228 Detection of Rumex spp. in Grassland using Multispectral Images and Deep Learning J. Heil, A. Stein J. Heil, A. Stein 223–228
- 229–234 Long term validation for app based chop quality estimation for silage maize S. Belau, D. Neitemeier, H. Korte, H. Westendarp, Y. Ehlert, J. Amsbeck S. Belau, D. Neitemeier, H. Korte, H. Westendarp, Y. Ehlert, J. Amsbeck 229–234
235–254 Digital Innovation 235–254
- 235–242 Unpacking the opportunities and limitations of data spaces in agriculture R. Matar, P. Neuschwander, R. Falcão, E. Calvet R. Matar, P. Neuschwander, R. Falcão, E. Calvet 235–242
- 243–248 Potential of agricultural machinery data for the evaluation of travel times L. Lange, H. J. Meyer L. Lange, H. J. Meyer 243–248
- 249–254 Training neural networks for tramline detection in an autonomous driving tractor using synthetic images S. Schulpius, J. Schattenberg, L. Frerichs S. Schulpius, J. Schattenberg, L. Frerichs 249–254
255–274 Cultivation 255–274
- 255–262 CF-Plough – An innovative solution for climate protection, soil fertility and yield security F. Fröming, M. Gerriets F. Fröming, M. Gerriets 255–262
- 263–268 Potential for increasing the efficiency of active soil tillage in crops, which are cultivated in ridges K. Dernjac, A. Lange gen. Detert K. Dernjac, A. Lange gen. Detert 263–268
- 269–274 A new approach of in-row-weeding sugar beets – using high pressure water jets and GNSS-locations of the crops D. Mayer, A. Baumann, T. Eberhard, A. Stoll D. Mayer, A. Baumann, T. Eberhard, A. Stoll 269–274
275–302 Innovative Technologies 275–302
- 275–282 V-Model Approach for Developing Safe Environment Perception Systems for Autonomous Machinery M. Komesker, C. Meltebrink, S. Ebenhöch, S. Stiene M. Komesker, C. Meltebrink, S. Ebenhöch, S. Stiene 275–282
- 283–288 Precise trunk localization using the example of in-row weeding in vineyards T. Blume, S. Flöser, M. Rasumak T. Blume, S. Flöser, M. Rasumak 283–288
- 289–296 Field Path Detection for Tractors Based on Acceleration Measurements and Multibody System Simulations W. Fuchs, G. Jedinger-Pauschenwein W. Fuchs, G. Jedinger-Pauschenwein 289–296
- 297–302 Implementation of a real-time plant detector for a selective grassland weeding machine using high-pressure water jets I.-L. Haußmann, G. Lohrmann, A. Stoll, L. Petrich, V. Schmidt I.-L. Haußmann, G. Lohrmann, A. Stoll, L. Petrich, V. Schmidt 297–302
303–322 Sustainable Energy and Irrigation Systems 303–322
- 303–310 Production and utilization of methane from cowshed gas on farms F. von Arnim, C. Gerdes, M. Geimer F. von Arnim, C. Gerdes, M. Geimer 303–310
- 311–316 Draft force evaluation of a deep ploughing technology for the installation of geothermal collectors under arable land J. Münch, B. Burkert, T. Herlitzius J. Münch, B. Burkert, T. Herlitzius 311–316
- 317–322 Holistic concept of technical solutions for subsurface drip irrigation of major crops in humid central European growing conditions W. Strothmann, C. Scholz W. Strothmann, C. Scholz 317–322
323–352 Assistant and Safety Concepts 323–352
- 323–332 Integration of a safety concept for an autonomous agricultural machine T. Schulte, J. Roelse T. Schulte, J. Roelse 323–332
- 333–340 Low-Cost, Rapid Development of Object Detectors for Automation of Agriculture Knowledge Distillation of GroundingDINO is Strong Pretraining F. C. Eichhorn, L. Schönland, D. Görges F. C. Eichhorn, L. Schönland, D. Görges 333–340
- 341–346 Applicable Safety Tests for Automated Agricultural Machinery and Robots Operational Design Domains and Dynamic Driving Tasks as Key to Functional Safety J. Schöning, N. Kruse, M. Komesker, D. Barrelmeyer, St. Stiene J. Schöning, N. Kruse, M. Komesker, D. Barrelmeyer, St. Stiene 341–346
- 347–352 TIM-Ready Trailer for Harvest Operations ISOBUS-ready Trailer for Harvest-Automation and -Documentation M.-A. Favier, T. Burgers, Y. Challe M.-A. Favier, T. Burgers, Y. Challe 347–352
353–XVI Sensor Technologies 353–XVI
- 353–362 Radar and ultrasonic systems from Bosch Engineering for automated agricultural machinery C. Marbach C. Marbach 353–362
- 363–368 Sensor breakthrough? Detection of invisible damages on potatoes before blackspot develops shown for multiple maturity stages and varieties using a tactile sensing technique J. Langfermann, W. Strothmann, J. Westerhoff, C. Scholz J. Langfermann, W. Strothmann, J. Westerhoff, C. Scholz 363–368
- 369–XVI Development of a supplement to a test standard for evaluating the guidance accuracy and working quality of sensor-based technologies for weed control by use of AI P. Steinhausen, O. Schmittmann P. Steinhausen, O. Schmittmann 369–XVI

Durchsuchen Sie das Werk

Geben Sie ein Keyword in die Suchleiste ein

Diese Webseite verwendet Cookies

[#IABV2_TITLE#]

LAND.TECHNIK 2024

Zusammenfassung

Schlagworte

Durchsuchen Sie das Werk