Advanced Fibre-Optic Sensors Coupled with IoT and Machine Learning for Precision Agriculture Applications

About the project

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Advanced Fibre-Optic Sensors Coupled with IoT and Machine Learning for Precision Agriculture Applications

School: School of Science and Technology

Study mode(s): Full-time

Starting: 2026

Funding: UK student / Fully-funded

Project overview

Smart agriculture is transforming food production through technologies that improve productivity and sustainability. A key challenge is obtaining reliable, real-time information about soil conditions, particularly moisture and nutrient levels which directly influence crop health and yield. Existing measurement methods are often costly, require laboratory analysis, and cannot easily provide continuous multi-parameter monitoring in the field. At the same time, efficient water management and reduced nitrate overuse are increasingly important as climate change intensifies droughts and nutrient runoff contributes to greenhouse gas emissions and water pollution.

This PhD project will develop a novel optical fibre sensing system for real-time, in-situ soil monitoring, initially targeting moisture and nitrate detection. Optical fibre sensors are compact, robust, low-cost, and immune to electromagnetic interference, making them well suited for agricultural environments.

The project will build on the supervisory team’s expertise to design sensors capable of simultaneous multi-parameter detection. Research activities will include fibre processing, nanostructure deposition, and functional coatings to enable sensitive and selective soil sensing.

The sensing platform will be integrated with IoT hardware for low-power wireless data transmission, while machine learning (ML) models will analyse the data to provide reliable predictions of soil conditions. The developed prototype will be tested in agricultural environments through collaboration with environmental science partners.

By combining nanophotonics, IoT, and data-driven modelling, the project aims to deliver practical tools that support precision irrigation and fertilisation, helping improve resource efficiency and advance sustainable agriculture.

Supervisory team

Qimei Zhang

Charalampos Tsimenidis

Andy Gill

Entry qualifications

We welcome applications from highly motivated students with a strong interest in photonics and sensing technologies. Applicants should hold (or expect to achieve) a first-class or upper second-class honours degree in Physics, Optical Engineering, Biomedical Engineering, Electrical/Electronic Engineering, Materials Engineering, or a related discipline. A relevant MSc/MRes qualification would be advantageous but is not essential.

The successful candidate will join a supportive, interdisciplinary supervisory team with expertise in optical sensor fabrication, IoT deployment, and environmental/agricultural sciences. Training opportunities in advanced experimental techniques, data science, and professional development will be available throughout the PhD.

How to apply

Click the "Apply online" button at the top of this page to begin your application. The application deadline for this project is Thursday 22 October 2026 .

Fees and funding

This is a fully funded PhD studentship opportunity, open to UK applicants only.

Guidance and support

Find out about guidance and support for researchers

Still need help?

Contact Qimei Zhang on:

• Email: qimei.zhang@ntu.ac.uk

Research areas