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Integrated decentralized and centralised approach for low carbon water management

Project Code: IDEAL 

Project Description:

The proposal aims to explore integrated decentralised approaches and centralised approaches with the advances of sensing, IOT, 5G, edge computing, and artificial intelligence (AI) to develop an innovate solution for the management of water systems, achieving the net-zero target in the water sector. Implementing a decentralised approach can distribute data processing across multiple locations in water systems, bringing intelligent analysing and processing near to devices and systems, subsequently aiding timely decision-making. In contrast with current situation, more and more data collected from devices are sent to cloud, which cost huge amount of energy for data transmission to cloud and high processing power to process big data on cloud, also transmission data can cause delay and data lost and could lead to delay to response of potential risks in water system. The solution will benefit water companies to improve energy efficiency and reduce the carbon foot and provide good services for consumers. This approach will reduce energy consumption due to data transmission and the risk of downtime and system failures, leading to a resilient and adaptable water system. This research can bring a significant benefit for water utilities to provide water smart services for customers and communities and contribute to net zero and climate neutral society. 

Anticipated Findings and Contribution to Knowledge:

  • Evaluate decentralised and centralised approaches with emerging technology for water systems in various geographic, climate and economic conditions.
  • Create a new low-cost sensing and lightweight processing techniques using AI /ML and edge computing in a decentralise framework.
  • Develop a sensing as a service platform to deal with local and central data in water system autonomously to support smart water management.
  • Publish Journals and conference papers to support impact case development in Smart Water and sustainable goals in clean water, Net Zero and sustainable city and community.

Person Specification:

The candidate for this position should possess a first-class Bachelor's or Master's degree in Electronic and Electrical Engineering or Control Engineering or Water Engineering, Computer Science, or a related field. We particularly welcome candidates with a robust background in sensing, modelling, optimization, artificial intelligence, and machine learning. We highly value candidates who can showcase a strong aptitude for original research, innovative thinking, and the capability to implement impact-driven solutions. 

Contact (and Director of Studies for this project): Prof Wenyan Wu, Wenyan.Wu@bcu.ac.uk 

How to Apply

To apply, please complete the project proposal form, ensuring that you quote the project reference, and then complete the online application where you will be required to upload your proposal in place of a personal statement as a PDF document.

You will also be required to upload two references, at least one being an academic reference, and your qualification/s of entry (Bachelor/Masters certificate/s and transcript/s).