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Development of 5G Smart Farming Dashboard to Detect Wild Animals on Pasture by Using Convolutional Neural Network

In: Advances and New Trends in Environmental Informatics

Author

Listed:
  • Ali Akyol

    (University of Oldenburg)

  • Rami Chahin

    (University of Oldenburg)

  • Jorge Marx Gómez

    (University of Oldenburg)

  • Hendrik Schwabe

    (Chamber of Agriculture in Lower Saxony)

  • Henrika Schwanke

    (Chamber of Agriculture in Lower Saxony)

  • Nora Uderstadt

    (Chamber of Agriculture in Lower Saxony)

Abstract

Agriculture in Central Europe serves the purpose of food production but it also takes place in natural wildlife habitats. This means that disturbance of wild animals cannot be completely avoided. When it comes to mowing of grassland or harvesting, especially deer fawns are in danger because they naturally have no reflex of escaping. To address this, Germany has introduced legal regulations and support measures, including subsidies for drones equipped with thermal imaging cameras. These technologies are part of the “5G Smart Country” project, which focuses on integrating digital solutions into agriculture. This paper presents a drone-based system developed within the project to efficiently detect and protect fawns during agricultural activities, enhancing both animal welfare and farm productivity.

Suggested Citation

  • Ali Akyol & Rami Chahin & Jorge Marx Gómez & Hendrik Schwabe & Henrika Schwanke & Nora Uderstadt, 2025. "Development of 5G Smart Farming Dashboard to Detect Wild Animals on Pasture by Using Convolutional Neural Network," Progress in IS, in: Volker Wohlgemuth & Hamdy Kandil & Amna Ramzy (ed.), Advances and New Trends in Environmental Informatics, pages 313-328, Springer.
    • Handle: RePEc:spr:prochp:978-3-031-85284-8_18
    DOI: 10.1007/978-3-031-85284-8_18
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