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IoT-Enabled LoRaWAN-Based Flood Monitoring and Early Warning System for Enhanced Climate Resilience in the UK​

Doctoral Training Grant Funding Information 

This funding model includes a 36 month fully funded PhD Studentship, set in-line with UK Research & Innovation values. For 2025/6, this will be £20,780 per year. The tax-free stipend will be paid monthly. This PhD Studentship also includes a Full-Time Fee Scholarship for up to 3 years. The funding is subject to your continued registration on the research degree, making satisfactory progression within your PhD, as well as attendance on and successful completion of the Postgraduate Certificate in Research Practice.

All applicants will receive the same stipend irrespective of fee status. 

Application Closing Date: 


Midday (UK Time) on Wednesday 17th September 2025 for a start date of 2nd February 2026.

How to Apply 

To apply, please follow the below steps:

  1. Complete the BCU Online Application Form.
  2. Complete the Doctoral Studentship Proposal Form in full, ensuring that you quote the project ID. You will be required to upload your proposal in place of a personal statement on the BCU online application form.
  3. Upload two references to your online application form (at least one of which must be an academic reference). 
  4. Upload your qualification(s) for entry onto the research degree programme. This will be Bachelor/Master’s certificate(s) and transcript(s). 
  5. International applicants must also provide a valid English language qualification. Please see the list of English language qualifications accepted here. Please check the individual research degree course page for the required scores. 

Frequently Asked Questions 

To help support you to complete your application, please consult the frequently asked questions below: 

Project title: ​​AIoT-Enabled LoRaWAN-Based Flood Monitoring and Early Warning System for Enhanced Climate Resilience in the UK​ 

Project Lead: ​​Dr. Waheb Abdullah​

Project ID: ​​​05 - 45474777​​ 

Project description:

​​Flooding is a growing concern across the UK due to climate change, increasingly affecting vulnerable communities, infrastructure, and public services. This PhD project offers an exciting opportunity to contribute to the development of a cutting-edge intelligent flood monitoring and early warning system. The project will investigate the integration of Artificial Intelligence of Things (AIoT), combining energy-efficient Internet of Things (IoT) sensors, LoRaWAN (Long Range Wide Area Network) communication technology, and Artificial Intelligence (AI) analytics for adaptive, decentralised flood risk prediction. This research will explore the development and testing of a low-cost, low-power flood monitoring framework tailored to the UK context. Rather than large-scale deployments, the project will adopt a scalable testbed and simulation-driven approach using a mix of open datasets, edge AI models, and sensor emulation. ​ 

​The successful applicant will join a vibrant interdisciplinary team and have access to specialist labs, supervisory support, and engagement with potential industry stakeholders. This research aligns with BCU’s 2030 strategy on sustainability, climate resilience, and digital innovation.​ 

Anticipated findings and contributions to knowledge:

This project will deliver novel insights into the integration of AI and IoT technologies for flood monitoring and risk prediction, contributing significantly to the field of smart environmental systems. The anticipated outcomes include: 

  • ​A validated proof-of-concept framework for AIoT-based flood monitoring that demonstrates the potential of combining AI, LoRaWAN, and decentralised sensor networks for enhanced climate resilience 

  • ​Development of a scalable low-cost sensing system for real-time flood monitoring, suitable for future implementation in remote or underserved areas 

  • ​Novel AI models trained on open datasets and synthetic data, capable of real-time analysis and prediction of flood events using rainfall, water level, and weather parameters 

  • ​A modular and adaptable edge-based system architecture, optimised for performance in constrained environments, offering a foundation for future scale-up 

  • ​Guidelines and strategic insights for integration with current UK flood risk and civil protection strategies, aimed at supporting policymakers and environmental agencies 

  • ​High-quality academic outputs, including peer-reviewed publications and open-source repositories to support transparency and reuse​ 

Person Specification:

​​Entry Requirements: 

  • ​To apply for our Engineering PhD Research Degree you should have, or expect to be awarded, a Master’s degree in a relevant subject area from a British or overseas university.  

  • ​Exceptional candidates without a Master’s degree, but holding a first class or upper second class Bachelor’s degree in a relevant subject area, may be considered.  

  • ​We also welcome enquiries from potential PhD researchers with appropriate levels of professional experience.  ​ 

​ Essential Criteria: 

  • ​Knowledge or demonstrable interest in one or more of the following: IoT systems, wireless communication (especially LoRa/LoRaWAN), AI/ML, embedded systems, or environmental sensing 

  • ​Ability to work independently, demonstrate critical thinking, and engage in interdisciplinary collaboration 

  • ​Good written and verbal communication skills ​ 

​Desirable Criteria: 

  • ​Practical experience with IoT prototyping using Arduino, Raspberry Pi, or other microcontroller platforms 

  • ​Familiarity with Python or MATLAB for data processing and AI model development 

  • ​Understanding of flood risk, environmental systems, or climate resilience frameworks 

  • ​Evidence of project or lab-based work related to sensing, simulation, or embedded systems 

  • ​Willingness to engage with stakeholders and contribute to research impact beyond academia ​ 

​This PhD is ideal for a candidate who is motivated to contribute to digital solutions for sustainability and resilience and who is seeking to build an academic or applied research career in smart systems and environmental intelligence

Overseas applicants:

International applicants must also provide a valid English language qualification, such as International English Language Test System (IELTS) or equivalent with an overall score of 6.5 with no band below 6.0. 

Contact:

If you have any questions or need further information, please use the contact details below: 

- For enquiries about the funding or project proposal, please contact: waheb.abdullah@bcu.ac.uk

- For enquiries about the application process, please contact:research.admissions@bcu.ac.uk