Leakage and inadequate use of water costs some organisations a significant amount of fund that could be used for a good cause. For instance, a public service organisation in England consumes an estimated 38.8 million cubic metres of water and generates approximately 26.3 million cubic metres of sewage per year. The use of water is also linked to the overall carbon footprint of an organisation through heating for hot water and energy consumption to pump water to the taps. This industry-sponsored PhD research programme aims to develop the state-of-the-art leak detection and data modelling techniques to minimise water leaks and wastage. Two key challenges in water management are the unnoticed leakages and human behaviour towards usage. There are various methods for detecting leaks in a water distribution system. Despite the availability of such methods, many leaks including slow leaks via dripping taps and small holes on underground pipelines are still undetected and unaccounted. New techniques based on advanced signal processing algorithms, precision mass flow balancing and communication techniques have the potential to overcome the limitations of the current techniques. In terms of user behaviour, there have been applications of machine learning techniques to model human behaviour to predict the efficiency of resource usage in recent years. The applicability of such techniques in predicting water usage and minimising water wastage in the service industry will be investigated. It is proposed to combine the improved leak detection techniques, data modelling and human behaviour analytics to minimise leaks and wastage of water.
University is looking for an excellent candidate with a relevant first degree and strong masters degree in electrical/electronic engineering, physical sciences or related areas relevant to the PhD topic. Experience in sensors, instrumentation and machine learning is advantageous.
The successful applicant will be expected to undertake some teaching commensurate with his/her experience at the University of Kent. Principally based at Kent Campus. It is also expected that the student will conduct experimental work at Medway NHS Foundation Trustfrom time to time.
Funding Details: Funding is available at the home/EU fee rate of £4,121 per annum. There will also be combined annual maintenance funding of £14,296.
Length of Award: 3 years (PhD)
Eligibility: Open to all applicants (UK students, EU students and international students)
Enquiries: Any enquiries relating to the project should be directed to Professor Yong Yan y.yan-at-kent.ac.uk.
Application: Apply for a PhD online and specify the research topic “Water leakage detection and wastage monitoring through advance sensing and data modelling”
Deadline: March 19, 2017