Vision
This project aims to develop a biodegradable, low-cost, AI-supported soil sensing platform for sustainable precision agriculture.
The goal is to improve understanding of soil conditions across agricultural environments, enabling more efficient use of water and fertilisers while reducing environmental impact.
Background and Motivation
Agriculture must produce more food while using fewer resources and causing less environmental damage. This is a significant global challenge: agriculture accounts for around 70% of global freshwater withdrawals [1], while soils are among the world's largest carbon stores, containing approximately 1,417 Gt of carbon in the top metre alone [2]. Poor management of soil resources can therefore affect food security, water availability, soil health, and climate resilience.
Excess irrigation can lead to erosion, waterlogging, nutrient leaching, and increased greenhouse-gas risks. At the same time, inefficient fertiliser use contributes to nutrient losses, eutrophication, and water pollution. More than 500 coastal regions worldwide have been affected by nutrient-driven eutrophication [6], while soil salinity currently affects around 1.4 billion hectares of land globally [7].
These interconnected challenges highlight the need for better information about soil conditions so that management decisions can be made more accurately and sustainably.
Research Challenge
Current low-cost soil sensing technologies often struggle to provide reliable information under real field conditions. Soil properties are influenced by many interacting factors, including moisture, nutrient levels, salinity, temperature, soil composition, and environmental conditions. These interactions can make sensor measurements difficult to interpret and can limit the effectiveness of existing monitoring systems.
At the same time, widespread deployment of sensing technologies raises additional challenges related to cost, scalability, sustainability, and electronic waste.
This project therefore explores how next-generation flexible and biodegradable sensing technologies can be combined with advanced data analytics and artificial intelligence to provide improved soil monitoring for precision agriculture.
Research Objectives
The PhD will investigate:
Biodegradable flexible soil sensors based on sustainable materials and manufacturing approaches.
Novel sensing methodologies capable of extracting richer information about soil conditions than current low-cost technologies.
Distributed sensing networks for monitoring spatial variability across agricultural land.
AI co-supervision frameworks that combine sensor data, environmental information, and expert knowledge to improve interpretation and decision-making.
Intelligent sensor deployment strategies that determine the optimal number and placement of sensors for different farm sizes, soil conditions, and monitoring requirements.
AI Co-Supervision
Artificial intelligence will be used to analyse sensor measurements alongside environmental and agricultural information such as weather conditions, soil type, crop growth stage, irrigation history, and fertiliser application records.
Rather than operating independently, the AI system will work in partnership with farmers, agronomists, and soil scientists. Human expertise will be used to validate recommendations, provide contextual knowledge, and improve model performance over time. The same framework will also be used to optimise sensor deployment, ensuring efficient monitoring while minimising cost and resource consumption.
Expected Outcomes
The project is expected to deliver:
Sustainable biodegradable soil sensing technologies.
Advanced methods for monitoring and interpreting soil conditions.
AI-assisted tools for precision agriculture and resource management.
Field-validated monitoring systems capable of supporting improved irrigation and fertiliser decisions.
This interdisciplinary PhD will be undertaken at the intersection of Artificial Intelligence, Sustainable Electronics, Sensor Systems, and Precision Agriculture. Researchers will benefit from access to the Printed Electronics and Materials Laboratory, the SusTAI Centre for Doctoral Training, and a world-leading supervisory team.
References:
[1] FAO, Water and One Health - https://www.fao.org/one-health/areas-of-work/water/en
[2] FAO, Global Symposium on Soil Organic Carbon: Key Messages - https://www.fao.org/global-soil-partnership/resources/highlights/detail/en/c/897470/
[3] NASA Earth Indicators, Methane- https://science.nasa.gov/earth/explore/earth-indicators/methane/
[4] Environment Agency, Reducing methane emissions to help combat climate change - https://environmentagency.blog.gov.uk/2024/04/10/reducing-methane-emissions-to-help-combat-climate-change/
[5] Our World in Data, Fertilizers - https://ourworldindata.org/fertilizers
[6] UNEP, Nutrient Management: The Issue - https://www.unep.org/explore-topics/oceans-seas/global-partnership-nutrient-management/nutrient-management-issue
[7] FAO, Global Assessment of Salt-Affected Soils - https://www.fao.org/newsroom/detail/fao-launches-first-major-global-assessment-of-salt-affected-soils-in-50-years/en
Selected background literature:
[8] Raheja, A. et al., Designing and field calibration of low-cost microcontroller-based soil moisture sensor for subsurface drip-irrigation system, Scientific Reports, 2025.
[9] Kizito, F., Campbell, C., Campbell, G., Cobos, D., Teare, B., Carter, B., & Hopmans, J., Frequency, Electrical Conductivity and Temperature Analysis of a Low-Cost Capacitance Soil Moisture Sensor, Journal of Hydrology, 352(3–4), 2008, pp. 367–378.
[10] Skierucha, W., Wilczek, A., Alokhina, O., et al., A FDR Sensor for Measuring Complex Soil Dielectric Permittivity in the 10–500 MHz Frequency Range, Sensors, 10(4), 2010, pp. 3314–3329.
[11] Dahal, S. et al., Degradability of Biodegradable Soil Moisture Sensor Components and Their Effect on Maize (Zea mays L.) Growth, Sensors, 2020.
[12] Syrový, T. et al., Fully Printed Disposable IoT Soil Moisture Sensors for Precision Agriculture, Chemosensors, 2020.
[13] Zaccarin, A. M. et al., Fabrication and Characterization of Soil Moisture Sensors on a Biodegradable, Cellulose-Based Substrate, IEEE Sensors Journal, 2023/2024.
[14] Baumbauer, C. L., Printed Biodegradable Wireless Soil Nitrate Sensor Nodes, University of California, Berkeley, 2022/2023.