Current projects in Intelligent Systems Research
Find out more about current Intelligent Systems Research Centre projects.
At ISRC we use world class facilities and ideas to make our work pioneering.
The project aims to develop a Knowledge Graph of a domain created by legal experts through intelligent machine learning algorithms.
Securing Tomorrows World builds on Ulster’s well-established STEM outreach activities to create a long-lasting cost-effective model to train degree-qualified academic & industrial engineers in the art of inspiring students to follow an cyber security career.
Department for the Economy
Smart sENsor Devices fOr rehabilitation and Connected health (SENDoc) project will introduce the use of wearable sensor systems in ageing communities in northern remote areas.
CINE is a collaborative digital heritage project between 9 partners and 10 associated partners from Norway, Iceland, Ireland, Northern Ireland and Scotland.
Can inertial movement sensors (IMUs) provide a valid and reliable way of measuring Spinal Mobility in Axial Spondylo-arthritis (axSpa)? A clinimetric evaluation
The main objective of this project is to test the accuracy and reliability of electronic sensors in measuring spinal movement and to develop a new outcome tool for spinal mobility. Current methods rely on tape measures/goniometers and are not reliable/responsive enough to evaluate new treatments for axSpa.
FOREUM - Foundation for Research in Rheumatology - Charity
REAMIT - improving Resource Efficiency of Agribusiness supply chains by Minimising waste using big data and Internet of Things sensors
The REAMIT project proposes to adapt and apply existing innovative technology to food supply chains in NWE to reduce food waste and hence improve resource efficiency. Reducing food waste is of highest priority for the EU (88Mt or € 143B wasted per year). Though technologies exist to reduce food waste, they have not been applied to food supply chains.
Trailgazers (TG) Bid will measure socio-economic impacts from investing & promoting trails in areas of rich natural heritage. Project objectives are to establish a common set of economic, social & environmental KPIs; develop innovative technologies & systems to capture trails activity and develop plans to sustainably manage trails. Results include a trails dashboard, tools to digitally target visitors and boosting of Atlantic Tourist numbers.
CertificationD - Certification of Technological products for People with Dementia to support SMEs in innovation and business growth
CertD supports SMEs in NWE that develop and market innovative, reliable, self-determined home living products for People with Dementia.
T4Anxiety aims to support the implementation of innovative solutions through start-ups with the objective of reducing the anxiety of patients suffering from mental disorders.
Technological innovations give new perspectives in many domains, including health. It is in this context that IT4Anxiety brings together mental health professionals and startups, alongside universities, research centers, higher education establishments and public authorities.
The StoryTagging project combines traditional storytelling with modern technologies to help increase the visibility and market reach of creative practitioners working in remote areas.
The project will develop a digital platform (both a website and apps) that will allow creatives to harness those stories that make Northern regions distinct: place, identity & community; folklore; cultural heritage; landscape and natural heritage. Northword is the brand name that will be adopted for the digital platform.
Stratus will use disruptive VR technologies to enable exploration of the Past, Present and Future, maximising societal benefits from natural and cultural heritage. In Stratus we will use VR to enhance the visitor experience, help direct the flows of visitors and inform policy.
This project focuses on the innovation opportunities offered to healthcare providers and other public bodies by the provision and implementation of an Internet of Things (IoT) infrastructure and strategy.
The objective of this project is to design and develop an automated, machine learning-powered time-lapse creator that will be able to ingest large amounts of video and intelligently select the best frames, often by merging multiple frames, and to create a condensed summary of building site activity.
There has been an upsurge in use of technology solutions across the NPA, solutions that have been attempting to reduce effects of COVID-19. These include attempting to reduce demand for other services, protection of vulnerable people (apps for wellbeing), using technology for test/trace of cases and technology to enable social distancing.
The indirect consequences of Covid-19 on the mental health of the general population will be considerable. First, anxiety, depression, alcohol misuse and suicidality are likely to increase in the general population.
iPatient developed an interactive teaching tool for colleagues in ADDL at Ulster. It simulates a range of patient scenarios to provide students with teaching and revision material on the topic of the ‘Red Eye’.
This project developed product for identifying individuals by their gait or the way they walk. This used emerging biometric surveillance techniques, a camera-based intelligent surveillance software solution.
With the increased penetration of renewable energy sources and the goal of reducing the reliance on fossil fuel dependence for power generation the goal for most countries.
To maintain the ageing electrical grid system within Northern Ireland a new approach is required to integrate these renewable resources.
Centre for Advanced and Sustainable Energy (CASE) - Invest NI
NOTE - NeighbOurhoods on Thin IcE – Heritage and Naturally Valued Climate-Sensitive Built Environments - Preparatory Award
Neighbourhood’s on Thin Ice considered new evidence-based planning methods, a decision-making framework and toolkit for heritage sensitive and healthy urban planning/design, customized to sparsely populated communities, northern climate conditions and climate change.
Communities face dilemmas regarding natural resources, a source of economic growth which also greatly affects the local environment and involves multi-national companies.
The SOFIA preparatory project co-ordinated activity at a transnational level to identify best practice, established an evidence base of health and wellbeing impacts on individuals by using sensor technology to collect information, and considered a toolkit to assist remote and rural farms and crofts to make Social Farming viable by measuring the wider employment and community impacts.
MIDAS intends to have a real impact on these problems to improve health, and health care delivery. The ambition of MIDAS centres on architecting, building and provisioning an operational big data platform that enables the policy makers in the project to make more informed decisions based on the actionable insights as derived from a plurality of population-based healthcare data and other related data.
This scoping project focuses on cognitive health in ageing, using data from the TUDA study (Trinity, Ulster, Department of Agriculture) linking nutrition, biomarker, lifestyle, health, and geo-referenced data with cognition as people age.
A Multidisciplinary, Data Analytics and Public Participatory Approach to Better Understanding the Risks of Dementia in Ageing
This inter-disciplinary project focuses on cognitive health in ageing, using existing TUDA data (Trinity, Ulster, Department of Agriculture Study) linking nutrition, biomarker, lifestyle, health, and geo-referenced data with cognition as people age.
The project seeks to address healthcare challenges by identifying effective dietary and lifestyle intervention options in order to promote health and wellness in our ageing population through the use of data analytics technologies applied to the TUDA dataset.
MalarInfo: A machine learning information toolset for predicting malaria risk, rates and trends in intervention planning: A pilot project in Zambia
This project aims to translate the methodology and statistical models developed at Ulster for Malaria risk and rate trends into a practical near real-time (pilot) tool that can be used for better prediction of malaria infections to improve the monitoring, planning, targeting and forecasting of intervention needs and health impacts.
The goal of this project was to investigate meta-learning in reinforcement learning under highly stochastic environments using mathematically tractable and autonomous Braitenberg vehicles. In collaboration with Dr. Mehdi Khamassi (Institut des Systemes Intelligents et de Robotique, CNRS-Universite Pierre et Marie Curie, Paris, France).
Integrated Health Analytics Centre (IHAC) - Dementia signature and risk prediction, and laboratory test data variability
The goal of the project was to use machine learning on neuroimaging data to detect Alzheimer’s disease, and data analytics to identify variability of lab tests across Northern Ireland.
The goal of this project was to develop large-scale neural circuit model of value learning and risky decision.
Royal Society - NSFC International Exchanges
The goal of this project was to develop computational decision support tool to diagnose Alzheimer’s disease.
The goal of this project was to computationally model multisensory decision inspired by neuroscience. In collaboration with Dr. Shufang Yang (University of Wolverhampton).
Ministry of Defence via BAE Systems, Autonomous Systems Underpinning Research (ASUR 1014_C4_PH1_071)
The goal of this project is to use electronic healthcare service and data analytics to speed dementia diagnosis.
The goal of this project is to use electronic healthcare service and data analytics to develop a dementia diagnosis support tool.
The goal of this project is to coordinate international researchers to develop and evaluate a transdisciplinary framework for multiscale systems medicine. In collaboration with multiple institutions across multiple countries. Prof. H. Schmidt, Maastricht U (Chair/PI).
EU COST Action (CA15120)
Computational modelling of novel serotonergic therapeutic mechanisms for the treatment of Alzheimer’s disease
The goal of this study is to develop computational model of biological signalling of serotonin receptors to identify potential treatment for Alzheimer’s disease.
The Centre for Personalised Medicine was established in April 2017 following an award of €8.6 million from the EU’s INTERREG VA Programme and managed by the Special EU Programmes Body.
This project brings together a total of 14 partners from academia, health services and industry to create the environment needed for personalised medicine : a research-based medical approach to guide clinical decisions to ensure a patient receives the right treatment at the right time.
A novel computational framework for predicting the conversion from early-stage mild cognitive impairment to Alzheimer’s disease
The goal of this study is to use computational approaches to predict Alzheimer’s disease. In collaboration with Dr. Stephen Todd (Altnagelvin Area Hospital).
Ulster University Research Challenge Fund
Large-scale recording and computational modelling of midbrain raphe microcircuitry during emotional learning
The goal of this study is to use computational modelling, optogenetics and other techniques to understand neural circuits within the raphe brain region in rodents performing emotional learning. In collaboration with Prof. Trevor Sharp at the University of Oxford.
£766,386 (UU: £234,964) - Joint funding with the University of Oxford
BBSRC Standard Grant (BB/P003427/1)
The goal of this study is to gain insights into how and where abstract decision mechanisms take place in the human and monkey brain through a concerted multi-species, multi-modal investigation integrated with computational modelling.
- US-Ireland R&D Partnership Programme
- HSC R&D (STL/5540/19)
- UKRI MRC (MC_PC_20020)
This project not only hopes to make residents more proficient and skilled in computing and creating the potential for employment, but to also raise aspirations to consider further education as an alternative to unemployment.
BT-Ireland Innovation Centre (BTIIC). An International Centre of Excellence for Industrial Research and Engineering
The BT Ireland Innovation Centre (BTIIC), undertakes an extensive programme of research and development that will cost an estimated £28.6 million over the next five years, with Invest NI support of £9 million towards the R&D programme.
Areas of research focus include Internet of Things, Artificial Intelligence and Data Analytics for customer experience and cybersecurity.
Future Screens NI comprises the two higher education institutions (Ulster University and QUB) and a number of key industrial partners central to the creative economy in the region.
In the Magic project Phase 3, the Ulster team was selected, along with industrial partners, as suppliers with funding to implement and trial the Magic Glass with stroke patients in Northern Ireland and Italy. After which, we will have the opportunity to tender in the EU-wide procurement.
Phase 1 of Magic involved customer discovery, the creation of a business plan, and the construction of a technical plan to deliver our Magic Glass product as a groundbreaking solution for home-based stroke rehabilitation.
ICURe is a programme of commercialisation support for teams of academic researchers wishing to explore the commercial potential of their research.
It aims to improve commercial awareness amongst academic personnel, to develop and enhance the entrepreneurial skills of early career researchers, and to strengthen links between academic and industrial communities.
The first phase of the project aims at developing an innovative and modular third-generation ICT solution for independent living, by integrating and improving two existing platforms.
A system of algorithms for behavioural analysis will be implemented, to allow constant interaction between users and the technological platform.
REMIND: The use of computational techniques to improve compliance to reminders within smart environments
The aim of this project is to create an International and Intersectoral network to facilitate the exchange of staff to progress developments in reminding technologies for persons with dementia which can be deployed in smart environments.
The focus will be on developing staff and partner skills in the areas of user centred design and behavioural science coupled with improved computational techniques which in turn will offer more appropriate and efficacious reminding solutions.
Training ergonomics, self-management and health behaviour strategies to mature workers suffering from chronic low-back pain (MY-RELIEF)
The main goal of the MY-RELIEF project is to improve knowledge and skills of working adults (55+ years) regarding evidence-based strategies that can help individuals manage their low back pain in all personal spheres (work, family, leisure etc.).
Chronic pain is associated with many different diagnostic entities ranging from diseases like e.g. osteoarthritis, low-back pain and other muscular-skeletal conditions to neuropathic pain conditions like painful diabetic polyneuropathy and pain following a stroke or multiple sclerosis.
This project is primarily focused on upper limb movement restoration of post-stroke individuals with movement impairments.
A BCI Operated Hand Exoskeleton based Neurorehabilitation System for Movement Restoration in Paralysis
The project investigated a neuro-rehabilitation system that facilitates intensive active physical practice and MI practice.
The overall objective of this project is the development of a control system for road maintenance trucks that will automate the dispensing of both tar and stone chips onto roads.
The main aim of the present project was to investigate the role of astroglial mitochondrial G protein (mtG) signalling in brain physiology, identifying the underlying cellular, network, behavioural and theoretical modelling mechanisms.
This project demonstrated that the self-repairing spiking neural network is capable of diagnosing faults and subsequently performing repairs beyond existing levels, where the repair capability was showcased in hardware using real-time robotic applications.
This project will demonstrate a fault tolerant autonomous robotic system that is able to continually detect, in real-time, changes in the air environment, and construct a hazard map of potential threats.