Thesis subject

Football’s Battle for Home Field and Environmental Advantage

Combatting pests/diseases with pesticides poses environmental risks and alternative solutions are needed. Digital twins could allow us to unravel the belowground world of healthy and infected plants to uncover new approaches with more environment friendly/sustainable benefits.
This project concerns the investigation into a digital twin prototype of a professional football pitch, based on digital techniques (e.g. Spectral Imaging at High Resolution, IoT Sensor Data, Game Engine technology). Liverpool FCs Anfield pitch is the proposed model system (internationally well-known, and the greenkeepers are eager to collaborate).

Football is the most popular sport globally, played and watched by billions of people. Yet few people realise the prevalence of soil borne pests and diseases that greenkeepers battle with to keep the turfgrass in optimal condition. A digital twin will enable the development of an early warning system of problems in turfgrass, promoting disease and pest control in non-artificial sport and leisure turf in a sustainable way.


    Objectives

    The project objectives are flexible to cater for students from various study disciplines. However, the vision is to adhere to the following steps:

    1. Investigate soil/below-turf pests/diseases and the current mitigation techniques unique to football pitches
    2. Design/model digital twin environment using formal methods
    3. Experimentation/model-development
    4. Define results.

      Literature

      • Bedir Tekinerdogan, Cor Verdouw, Systems Architecture Design Pattern Catalogue for Developing Digital Twins, MDPI Sensors, Vol. 20, pp. 5103, 2020 - https://www.mdpi.com/1424-8220/20/18/5103
      • Duansen Shangguan, Liping Chen et al., A Digital Twin-Based Approach for the Fault Diagnosis and Health Monitoring of a Complex Satellite System, MDPI Symmetry, Vo. 12, pp 1307, https://www.mdpi.com/2073-8994/12/8/1307/htm

      Requirements (optional)

        Theme(s)

        Digital Twin, IoT Sensors, Data Analysis, Pesticide, Football

        Contact person(s)

        • Will Hurst (will.hurst@wur.nl)
        • Gerlinde De Deyn (gerlinde.dedeyn@wur.nl