The School of Computing, based at the Jordanstown campus, is comprised of two focused research groups in Pervasive Computing and Artificial Intelligence. The School is home to two industrially focused Innovation centres, BT Ireland Innovation Centre (BTIIC) and the Connected Health Innovation Centre (CHIC).
Computer Science at Ulster continues to be in the top 25% in the UK for research power. In the recently published national assessment of research quality, REF2014 (Research Excellence Framework), with 90% of our Research Environment being rated as world- leading or internationally excellent with the quality of its 4* and 3* publications ranking the submission at 17th out of 89.
In Pervasive Computing, research is focussed on sensor-based technologies, connected health, data analytics, computer vision, and next generation networks, systems and services, with applications in activity recognition, assistive technologies for healthcare and independent living, healthcare modelling and bioinformatics.
Research in Artificial Intelligence is focussed on machine learning, pattern recognition, logic and reasoning, knowledge engineering and ontology, decision support systems, and semantic analytics, with applications in text mining, intelligent document analysis, biometrics and video-based scenario and event recognition, and food authentication.
Research within School of Computing in Pervasive Computing is focused on ambient assisted living. This incorporates Internet of Things (networking and structure of sensors in buildings, clothing and personal devices) and intelligent processing (machine learning, data mining, pattern recognition, decision support, context-based prediction, data fusion, and multimodal interaction).
Much of the research focuses on behavioural monitoring (through environmental and biometric sensors) and activity recognition, with application to assistive technologies for smart homes, independent living, and healthcare monitoring and diagnosis. Research is supported by new laboratory facilities for deployment of sensing technology in connected health care, including body scanner, eye-tracking, and other state-of-the-art devices.
The main research themes in artificial intelligence are the following: data engineering; knowledge engineering; semantic analytics (making sense of unstructured data such as image, video, spectra and text); biomedical informatics; and mathematical modelling and optimisation.
Applications include work on multimodal biometrics (including face/palmprint/iris recognition); text and video information retrieval; food authentication; reliable decision support (e.g. medical and transport); soft sensor design; software complexity metrics; text mining to extract argumentation structure and application to document reuse and software defect analysis; remote sensing data analysis and anomaly detection; mathematical and computational modelling of complex systems; and biomedical applications.
To support this world-leading research, the school houses a state-of-the-art Smart Environment with a range of cutting-edge equipment and infrastructure. This environment has been specifically designed to facilitate the design, development and evaluation of solutions to support health, wellbeing and ambient assisted living. The environment has a smart kitchen, smart living room and smart bedroom which have been created to support the investigation into the area of assistive technologies and activity recognition. To complement these test beds, a set of 400 sensing nodes is currently available to be deployed in a smart environment covering a footprint of over 6,800 square feet. A recently installed maker lab supports the rapid prototyping of IoT endpoints. The environment also offers a large suite of pervasive sensing technologies, image and video modelling tools and a large suite of computing and software resources including high performance PowerEdge Tower servers.. Along with the smart environment, the School has a newly refurbished Connected Health Living Laboratory (CH:LL). The Connected Health Living Lab (CH:LL), within the School of Computing at Ulster provides a unique environment to support multi-disciplinary research in the area of connected health.
These facilities are used to support the development, deployment and evaluation of connected solutions, data acquisition and semantic analysis of a user environments.