Thesis subject

Costs and Benefits of Using Drones and AI Technology in Farming: An Empirical Analysis and A Decision Support System (MSc)

Costs and Benefits of Using Drones and AI Technology in Farming: An Empirical Analysis and A Decision Support System.

Short description

The agricultural sector is faced with an unprecedented technological revolution, driven by the rapid advancements in Artificial Intelligence (AI). AI technologies are being increasingly adopted to enhance productivity, optimize resource usage, and improve decision-making processes in farming. While there are various benefits to using AI, there are costs as well, which should be considered together with the costs before adopting AI technologies.

In this research assignment, we aim to examine the relationship between costs and benefits through a cost-benefit analysis, aiming to enhance targeted decision-making. The study aims to analyse case studies on AI usage (especially via drones) in farming to determine the added value of innovative applications/services or systems compared to the original situation.

This thesis is a collaboration with INF and Business Innovation Group at Fontys Business School. So we aim for a highly interdisciplinary research, combining IT, business, social and environment aspects.

    Objectives

    1. Quantitatively assess the costs versus the benefits to come up with a cost benefit ratio.
    2. Eventually come up with ways to minimize costs and maximise benefits considering Pareto optimality or Kaldor Hicks compensation),
    3. Find an NPV or ROI for a decision support system that helps in deciding whether the AI implementation is justifiable.

      Tasks

      The work in this master thesis entails:

      • Carry out secondary research to find cost-benefit studies and decision-support systems for the use of AI in farming.
      • Identify determinants to include in the model.
      • Assess the solutions available to extract data from the scientific literature in a scalable and efficient manner.
      • Collect and analyse data from the case studies.

      Literature

      • Kabza, Milena. "Artificial intelligence in financial services–benefits and costs." Innovation in Financial Services. Routledge, 2020. 183-198.
      • Caruso, Pier Francesco, et al. "Implementing artificial intelligence: assessing the cost and benefits of algorithmic decision-making in critical care." Critical Care Clinics 39.4 (2023): 783-793.
      • Mun, Johnathan, et al. "Acquiring artificial intelligence systems: Development challenges, implementation risks, and cost/benefits opportunities." Naval Engineers Journal 132.2 (2020): 79-94.
      • Doornbos, J., Bennin, K. E., Babur, Ö., & Valente, J. (2024). Drone Technologies: A Tertiary Systematic Literature Review on a Decade of Improvements. IEEE Access.

      Requirements

      • Courses: No mandatory course, but those could be helpful: Programming in Python (INF-22306), Big Data (INF-34306), Data Science Concepts (INF-34306) or Machine Learning (FTE-35306)
      • Required skills/knowledge: basic data analytics, interest about decision support systems, analytical skills

        Key words: Business-IT Alignment, Data Analysis, Data analytics, Drone, Artificial Intelligence

        Contact person(s)

        Önder Babur (onder.babur@wur.nl)