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

​​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.​ 

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​ 

​​Essential: 

​An Honours degree (2:1 or above) or a Master’s degree in Electronic/Electrical Engineering, Computer Science, or a closely related discipline 

• ​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: 

• ​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.​