Smart Technology Research Themes
The Smart Technology Research Centre works with many different commercial and research organisations, and co-ordinates and contributes to special interest-groups. Much of our work is funded by external organisations with examples of many successful applications. Further information can be found on our projects, publications, collaborations and events pages.
The centre is organised around the grid of Core Technical Competenciesand Application Areas (as illustrated in the Table below).
| STRC CORE COMPETENCIES | ||||
| A P P L I C A T I O N A R E A S |
Computational Intelligence | Intelligent Data and Information Processing | Sensory and Electronic Technologies | |
| Biomedical Engineering |
||||
| Telecommu- nication |
||||
| Process Industry | ||||
| Transport | ||||
| Airlines | ||||
| Retail | ||||
| Creative Industries |
||||
Within the above table, a dark shade of grey indicates a strong area (or cross-section) with significant level of activity including funded projects, publications, event organisation, editorship of journals, international recognition and knowledge transfer. A medium shade denotes a significant level of activity and a light grey some activity.
At the present moment, there are two strongly interlinked and complementary areas of research reflecting a body of activities, strong track record of achievements, external recognition and capacity for successful bidding for external funding. The first theme focuses on the softer aspects of Smart Systems and Technologies covering such areas as Computational Intelligence, Informatics and Complex Adaptive Systems while the second broad theme is more hardware and device oriented covering Sensory and Electronic Technologies, Robotics and Bio-Medical Engineering .
Computational Intelligence, Informatics and Complex Adaptive Systems
The work in this theme is a continuation of the research carried out within the Computational Intelligence Research Group (CIRG), which was formally established in 2003. The Group has been engaged in research of the theoretical and application aspects of advanced intelligent technologies.
The Group’s interests and expertise lay in a broad area of intelligent and biologically/nature inspired learning and complex adaptive systems. Our projects and research activities cover a wide range of machine learning and hybrid intelligent techniques encompassing data and information fusion, learning and adaptation methods, multiple classifier and prediction systems, processing and modelling of uncertainty in pattern recognition, diagnostic analysis and decision support systems.
Sensory and Electronic Technologies, Robotics and Biomedical Engineering
The work in this theme continues the research carried out within the Academic Biomedical Engineering Research Group (ABERG), which was established in 1999.
Our prime aim is to improve the quality of life of people with chronic disabilities in developing new treatment methods and assessment techniques to advance cost-effective, evidence-based health care. The Group has an international reputation in the areas of Functional Electrical Stimulation (FES) and rehabilitation engineering, sensor development and physiological measurements. The use of FES in stroke treatment has been adopted by the Royal College of Physicians. The Group was the first to develop a Laser Doppler sensor for in-shoe plantar blood-flow measurement.
