Einsatzmöglichkeiten von KI in der österreichischen Landwirtschaft
: Analyse hinsichtlich der Möglichkeit zur Steigerung von Effizienz, Nachhaltigkeit und Wirtschaftlichkeit

  • Marlene Feuchtinger

Student thesis: Master's Thesis

Abstract

Advances in the field of artificial intelligence have sparked significant interest in recent years, both in research and among the general public. The introduction of ChatGPT in 2022, in particular, has increased awareness of the potentials and challenges associated with AI technologies. In light of global challenges such as climate change, urbanisation, land degradation and the increasing need for food to support a growing world population, which is expected to reach nearly ten billion by 2050, the use of AI in agriculture could prove to be of great importance. This study explores the specific applications of AI in Austrian agriculture and assesses their impact on efficiency, sustainability, and economic viability. Furthermore, it analyses the legal framework governing the use of AI technologies in Austrian agriculture. This master's thesis is structured into six chapters. The introduction outlines the problem statement, objectives, and research questions. This is followed by a comprehensive literature review to capture the current state of research on the application of AI in agriculture. Building on these insights from the literature, guideline-based expert interviews are conducted, which are subsequently analysed qualitatively according to Mayring. The study reveals that AI systems hold considerable potential for increasing resource efficiency in Austrian agriculture, particularly through the precise management of agricultural processes and the optimisation of operational workflows. In crop production, the use of AI and computer vision can significantly enhance resource efficiency, for example, through targeted and resource-efficient application of pesticides and fertilisers. In livestock farming, for example, AI-supported systems enable efficient health monitoring and early detection of diseases, precise heat detection and a reduction in the use of antibiotics. Despite these advantages, challenges remain, including high implementation costs, acceptance issues among farmers, and the need for specific and high-quality data. Additionally, risks such as cyber-attacks and data misuse must be addressed. The findings of this study illustrate that AI technologies have the potential to significantly improve efficiency, sustainability, and economic viability in Austrian agriculture. However, realising this potential depends on overcoming existing challenges. In addition to regulatory frameworks and economic feasibility, targeted educational measures and efficient knowledge transfer are crucial for the successful deployment of AI in agriculture. The insights gained contribute to a deeper understanding of the application possibilities of AI technologies in Austrian agriculture.
Date of Award2024
Original languageGerman (Austria)
SupervisorAndreas Schnabl (Supervisor)

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