Using the Internet of Things and big data to dynamically map flood risk


Funded PhD


3 years (full-time)

Application deadline:

Wednesday 23 January 2019

About this project

This project will explore a range of Internet of Things (IoT) and big data approaches to dynamically mapping flood risk and response during events.

Traditional measurements and modelling that underpins present flood warning and alert systems are based on fixed and spatially restricted weather station and river (or groundwater) gauge networks. The IoT opens up the opportunity to exploit a range of other data to inform dynamically flood warnings, alert and responses.  This may include using data from cars to map rainfall, effectively turning cars into mobile rain gauges through location information and car wiper blade speeds, through to using mobile phone signal quality deviations to map rainfall in higher resolutions than presently possible. 

There are now significant volumes of open data and open-model systems available that can inform real-time response and guide emergency services and optimise their availability and site accessibility alongside the availability of supplies and assets such as sandbags and barriers. This can be reported along with the capability to use citizen-gathered data on social networks to map damage for insurers.

Together these approaches hold promise for the development of a smart flood management network with real-time now-casting of rainfall and flood extents at its heart.

The University's Postgraduate Training Scheme (PGTS) provides a range of generic and discipline-specific modules to support research students through their programme. 

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The library has an exclusive lounge for postgraduate research students and a dedicated Skills Team to provide a wide range of study and research skills help.

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The Graduate School provides support to postgraduate research students. Offering skills development opportunities and dedicated facilities, the school is here to help you achieve your potential. 

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Research at Hull tackles big challenges and makes an impact on lives globally, every day. Our current research portfolio spans everything from health to habitats, food to flooding and supply chains to slavery. 

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Full-time UK/EU and International PhD Scholarships will include tuition fees and maintenance (£14,777 in 2018/19) for three years, depending on satisfactory progress.

Entry requirements

Applicants should have a 1st class undergraduate degree in Computer Science or related discipline, or Masters level research qualification in a relevant discipline together with relevant research experience.

Excellent programming experience is essential. Knowledge or experience in one or more of the following areas is desirable: machine learning / deep learning, embedded systems, physical sciences, engineering or environmental sciences. A 2:1 may be considered, if combined with relevant experience.

Interviews will be held between 7 and 27 February 2019.

Successful applicants will be informed of the award as soon as possible and by 15 March 2019 at the latest.

Studentships will start on 16th September 2019.