Big Data, Machine Learning and Visualisation Systems for Water Demand Management - Engineering - PhD (Funded) (Advizzo Ltd London) Ref: 2663

About the award

The Industrial Partners on this project is: Advizzo Ltd. (London)

The global market for smart urban systems for transport, energy, healthcare, water and waste will amount to around $400 Billion per annum by 2020. On the back of better connectivity and better access to public information, we can manage cities more effectively, anticipate and solve problems more cost effectively, and raise the economic prospects and the quality of life in towns and cities.

Water is a key aspect of smart city management, with flooding and droughts being the main problems for cities. When local water consumption is balanced against availability, water poor regions can be easily identified in the UK. In southern and eastern England, where rainfall and available water are comparatively low and population comparatively high, water utilities face a problem of a serious water shortage. The likely impacts of climate change and increased urbanisation will result in the increase in urban demand for water and will make water security for urban population even more difficult and costly to achieve. Water use in households is also linked to energy use, given that 50-60% of domestic water consumption occurs in energy consuming appliances (washing machines, shower, bathtubs and dishwashers). A change of water use behaviour therefore not only has the potential to reduce the cost of lost water but also to extend the life of our present water resource and wastewater systems and to reduce the demand for energy with its consequent environmental benefits.


The Centre for Water Systems at the University of Exeter has a long history of research into water systems modelling and management. This PhD project, which is funded by EPSRC via the WISE Centre for Doctoral Training, This project aims to investigate the use of data analytics and smart water network technologies for improved management of urban water distribution systems by better quantifying end user demand and by providing consumption feedback to customers to manage their demand. The project will use a cloud-based software platform aimed at helping water utilities and their customers better meet future supply-demand requirements by improving water efficiency both in the distribution systems and in customer homes. The web-based platform relies on meter and billing data coming from water utilities. As a result, consumers are provided with insights and personalised tips to save water.  This project will leverage publically available data to provide bespoke modelling and data visualisation tools to assist water utility planning and identify water usage patterns.


Part of the new approach will include development and utilisation of machine learning, statistical tools and visualisation to:
• combine various sources of data (Big Data) to achieve more accurate and personalised insight into the water          consumption in individual homes;
• find the best mechanisms and channels through which feedback changes behaviour in order to maximise water saving;
• investigate how to best utilise data from smart meters to improve management of the utility water distribution systems;
• assess the quality and benefits of consumption feedback for water demand management;
• assess energy savings/benefits of improved water system efficiency; and
• develop Hydroinformatics tools and integrate them with the cloud-based platform.

Academic entry requirements:
Applicants should have or expect to achieve at least a 2:1 Honours degree, or equivalent, or an MSc degree in Computer Science or a closely related subject.  They should have strong programming skills, an aptitude for mathematics, statistics, and an enthusiasm for research into data analytics and machine learning.

We are looking for highly motivated applicants with a BSc or MSc degree in Computer Science or related fields (Engineering, Physics, Applied Mathematics). Previous experience in machine learning and AI methods, software engineering/informatics (R/Python, PHP, C++/C#, HTML5, CSS3), and/or water systems modelling, are highly desirable.
If you wish to discuss any details of the project informally, please contact Prof Dragan Savic, Centre for Water Systems, Email: d.savic@exeter.ac.uk , Tel: +44 (0) 1392 72 3637.

Summary

Application deadline:18th August 2017
Number of awards:1
Value: £14,553
Duration of award:per year
Contact: EMPS PGR Support team emps-pgr-ad@exeter.ac.uk

How to apply

To apply, complete the online form. You will be asked to submit some personal details and upload a full CV, covering letter and details of two academic referees. Your covering letter should outline your academic interests, prior research experience and reasons for wishing to undertake this project.

You may also be asked to upload verified transcripts of your most academic qualification.

Interviews will be held the in the last week of August 2017.

If English is not your first language you will need to have achieved at least 6.5 in IELTS and no less than 6.0 in any section by the start of the project. Alternative tests may be acceptable (see http://www.exeter.ac.uk/postgraduate/apply/english/).

This project is not available to non-UK applicants who do not meet residency requirements (see http://www.epsrc.ac.uk/skills/students/help/eligibility/