IDCoM Research Projects

Research Projects at the Institute for Imaging, Data and Communications (IDCoM). You can search keywords within Project Titles.

We also have a number of Imaging, Data and Communications PhD opportunities for postgraduate students looking to join the School.

Search keywords within Research Project titles
Project Title Principal Supervisorsort ascending Project Summary
Signal Processing in the Information Age

Prof Michael E Davies

The aim of the UDRC is to develop unprecedented research in signal processing with application to the defence industry and share knowledge, promote communications, guidance and training. The formation of consortia will bring together researchers from across the different aspects of signal processing to address the research challenges of operating in a networked battlespace. This will form part of a wider collaborative centre of excellence for signal processing that embraces academia, Research and Technology Organisations, defence manufacturing industries and the Defence Technology Centres. This collaboration will support a cutting edge signal and data processing capability in the UK, and lead to potentially greater research impact.

Laser Imaging of Turbine Engine Combustion Species (LITECS)

Dr Chang Liu

The ultimate ambition of the LITECS research programme is to reduce the environmental impact of aviation and industrial gas turbine engines by developing and deploying new measurement technologies to enhance the understanding and modelling of combustion and emissions generation processes and the role of alternative fuels.

RAPID: ReAl-time Process ModellIng and Diagnostics: Powering Digital Factories

Dr Nicholas Polydorides

Modern manufacturing involves highly controlled and automated processes meticulously designed to deliver products to specific needs within strict specifications and in a cost-efficient and sustainable way. Sensors capture continuous data streams about the state of the process, e.g., equipment and the product, to ensure performance in variable and often harsh conditions — however, the ability to analyse this data in real-time offers unique advantages currently out of reach. Learning to calibrate its operation from sensor data, monitor its health status and make accurate forecasts on product outcomes and maintenance requirements are process attributes of future autonomous factories.

In-situ Chemical Measurement and Imaging Diagnostics for Energy Process Engineering

Prof Hugh McCann and Prof Walter Johnstone

The primary focus of the programme proposed here is to build across two universities (Strathclyde and Edinburgh) a world leading UK research, development and applications capability in the field of in-situ chemical and particulate measurement and imaging diagnostics for energy process engineering. Independently, the two university groups already have globally eminent capabilities in laser-based chemical and particulate measurement and imaging technologies. They have recently been working in partnership on a highly complex engineering project (EPSRC FLITES) to realise a chemical species measurement and diagnostic imaging system (7m diameter) that can be used on the exhaust plume of the largest gas turbine (aero) engines for engine health monitoring and fuels evaluation. Success depended on the skills acquired by the team and their highly collaborative partnership working. A key objective is to keep this team together and to enhance their capability, thus underpinning the research and development of industrial products, technology and applications. The proposed grant would also accelerate the exploitation of a strategic opportunity in the field that arises from the above work and from recent recruitment of academic staff to augment their activities. The proposed programme will result in a suite of new (probably hybrid) validated, diagnostic techniques for high-temperature energy processes (e.g. fuel cells, gas turbine engines, ammonia-burning engines, flame systems, etc.). 

TASCC: Pervasive low-TeraHz and Video Sensing for Car Autonomy and Driver Assistance (PATH CAD)

Prof Bernard Mulgrew

This project combines novel low-THz (LTHz) sensor development with advanced video analysis, fusion and cross learning. Using the two streams integrated within the sensing, information and control systems of a modern automobile, we aim to map terrain and identify hazards such as potholes and surface texture changes in all weathers, and to detect and classify other road users (pedestrians, car, cyclists etc.).

Massive MIMO for Future Wireless Communication Networks

Dr Tharmalingam Ratnarajah

The spectrum crunch is a global phenomenon, where wireless networks constrained by scarce spectrum resource cannot keep pace with the explosion in mobile broadband use, particularly at a time when smartphones and tablets are becoming even more prevalent and heavily used. Every new opportunity has to be maximally exploited to cope with this spectrum deficit and meet the demands of explosive broadband usage by pushing more data through existing spectrum. Massive multiple-input multiple-output (MIMO), an advanced antenna technology only developed in 2010 offers one such opportunity.

Rural and Remote Ubiquitous Broadband Wireless Access

Dr Tharmalingam Ratnarajah

This research network would bring together key research groups that are in the vanguard of developing novel technologies and algorithms for spectrally efficient generation wireless networks in the UK and India.

SpaRTaN: Sparse Representations and Compressed Sensing Training Network

Professor Mike Davies

The aim of this Initial Training Network is to train a new generation of interdisciplinary researchers in sparse representations and compressed sensing, contributing to Europe’s leading role in scientific innovation.

MacSeNet: Machine Sensing Training Network

Professor Mike Davies

The aim of this Innovative Training Network is to train a new generation of creative, entrepreneurial and innovative early stage researchers (ESRs) in the research area of measurement and estimation of signals using knowledge or data about the underlying structure.

Signal Processing for a Networked Battlespace

Professor Mike Davies

This research is carried out under the Unversity Defence Research Collaboration (UDRC) funded by the MOD and EPSRC.

The UDRC is a collaborative research project with the work being carried out by two Consortia. Edinburgh Consortium is made of the University of Edinburgh, Heriot-Watt University and The Queen's University of Belfast. LSSCN Consortium is made up of Loughborough University, University of Surrey, University of Strathclyde, Cardiff University and Newcastle University.

 

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