Concept Phase Teams

*Teams co-funded by DFAT

3D3P

Empower and promote the social, economic and political inclusion of people with full or partial limb loss

Challenge Patients with full or partial limb loss can experience reduced social and economic inclusion when constrained to using prosthetic devices with sub-optimal functionality. We propose to advance the delivery of ‘right first time’ prostheses that can be upgraded regularly at low cost to meet a patient’s unique needs as they change over time. 

Solution The 3D3P team proposes to develop a low-cost 3D printed, high strength carbon-fibre prosthetic device for patients with lower limb amputations. The team proposes to leverage machine learning and data from prostheses as they are being used to dramatically reduce the cost and effort required to produce prosthetics customised for an individual’s needs. 

Team Padraig Cunningham (UCD), Andrew Dickson (UCD), Breda Clancy (Atlantic Prosthetic Orthotic Services Ltd) 

GreenWatch *

Enhancing United Nations Sustainable Development Goal progress measurement

Co-funded by Department of Foreign Affairs and Trade

Challenge Developing AI-based methods to detect greenwashing to improve the measurement of progress towards the United Nations Sustainable Development Goals (SDGs). 

Solution To tackle the issue of greenwashing and to enable stakeholders to identify and take action against it, new detection and measurement techniques must be developed. The GreenWatch team proposes to build a machine learning / natural language processing system to sift through large quantities of SDG related disclosures to identify instances of greenwashing. 

Team Andreas Hoepner (UCD), Georgiana Ifrim (UCD), Pat Cox (Sustainable Nation Ireland)

TAPAS *

Enabling developing countries to track climate change adaptation in their agri-food sectors

Co-funded by Department of Foreign Affairs and Trade

Challenge Enabling countries to develop evidence-based means of measuring, reporting and verifying climate change adaptation in the agri-food sector. 

Solution The TAPAS team will develop an AI-based approach that enables the agri-food sector to assess climatic perturbations. The proposed technology will initially focus on characterising climate change in the developing world but will be scalable for implementation globally to support national governments' compliance with the UNFCCC resolutions. 

Team Aaron Golden (NUIG), Charles Spillane (NUIG), Andy Jarvis (International Center for Tropical Agriculture (CIAT))

Cailín

Reducing the impact of endometriosis through timely diagnosis

Challenge Endometriosis affects 1 in 10 women and can lead to significant health issues. Despite this, diagnosis can take up to 7 years.  Timely diagnosis has the power to transform women’s lives, enabling appropriate treatment to stop the progression of the disease and preserve fertility. 

Solution The Cailín team will develop a non-invasive digital biomarker for endometriosis by measuring disease-specific symptoms and applying advanced machine learning techniques. This disruptive AI-enabled technology will end the diagnostic delay. 

Team Siobhan Kelleher (NUIG), John Breslin (NUIG), Kathleen King (Endometriosis Association of Ireland) 

https://twitter.com/CailinAI

Fair AI

Supporting social justice and equality by eliminating bias in AI

Challenge As AI-based systems make more decisions for us, there is an important need to ensure that these systems do not reproduce and exacerbate existing social biases and forms of discrimination.  

Solution The Fair AI team proposes to develop a platform that will evaluate and identify evidence of bias in relation to gender, race and political ideology in AI training sets. There are growing calls from both governmental institutions and industry for solutions to mitigate algorithmic bias. The Fair AI team will develop a scalable system that could be employed across a range of applications to evaluate training data for evidence of bias, thus working towards the goal of fairness in AI. 

Team Eugenia Siapera (UCD), Susan Leavy (UCD), Mary Hearne (LinkedIn)

Digital Diabetes

Reducing the burden of diabetes through earlier diagnosis

Challenge Diabetes is a global pandemic requiring urgent attention. It currently affects approximately 1 in 10 people and causes significant disease of the eyes, kidneys, nerves and cardiovascular system if undiagnosed and untreated. Early detection of diabetes is crucial so that treatment can be initiated earlier to improve human health. 

Solution The Digital Diabetes team proposes to develop a novel digital biomarker for diabetes diagnosis. This innovative approach will use state of the art big data and artificial intelligence techniques to diagnose diabetes significantly earlier than current methods. 

Team Derek O'Keeffe (NUIG), Andrew Simpkin (NUIG), Fidelma Dunne (NUIG)

VideoForce

Enabling remote sports injury assessment

Challenge Injuries associated with contact sports, such as rugby, create a significant societal burden and can act as a barrier to participation and can prevent the full benefits of getting involved in these sports from being realised. To increase the safety of these sports, rapid assessment of collisions is needed to guide injury prevention strategies. 

Solution The VideoForce team proposes to develop an AI-based approach that can be applied to sports video footage to assess collisions. In this way coaches and players will gain quantitative information to guide injury prevention strategies. 

Team Ciaran Simms (TCD), Aljosa Smolic (TCD), Garreth Farrell (Leinster Rugby)

AI-4-Life

Reducing neonatal morbidity and mortality

Challenge Intrapartum fetal monitoring is used to identify oxygen deprivation to the fetal brain during labour and delivery, to reduce the risk of neonatal morbidity and mortality. However, the current “gold-standard” approach to fetal monitoring is not accurate, is susceptible to misinterpretation and is unreliable.  

Solution The AI-4-Life team will develop a novel AI-based system to monitor the vital signs of mother and baby during labour to quickly identify any issues. 

Team Liam Marnane (UCC), Geraldine Boylan (UCC), Mairead O'Riordan (Cork University Maternity Hospital) 

https://www.infantcentre.ie/research/research-studies/ai-4-life-ai-for-fetal-wellbeing

https://twitter.com/ai_4_life

SmartAblate

Surgery-free therapy for lung cancer

Challenge Lung cancer kills more citizens than breast, colon and prostate cancer combined, with over 9.6 million new cases diagnosed annually worldwide. Lung cancer is currently treated via invasive open surgery. We propose to improve the treatment of this disease. 

Solution The SmartAblate team will develop an AI-driven endoscopic ablation therapy for localised lung cancer treatment. This disruptive approach will negate the need for open-surgery and will provide for safer and more effective treatment for patients suffering with lung cancer. 

Team Martin O'Halloran (NUIG), Giuseppe Ruvio (NUIG), Anne-Marie Baird (St. James's Hospital)

pCCare

Palliative care that meets the needs of an aging society

Challenge Currently, specialist palliative care services in the community operate by delivering a “one size fits all”, but as the needs of patients change, this model is no longer fit for purpose. New palliative care models are needed to ensure that patients can live longer while meeting their evolving health and wellbeing needs. 

Solution The pCCare team will develop a transformative and innovative approach to the allocation of specialist palliative care in the community supporting the needs of patients, families, and healthcare workers. 

Team Ciara Heavin (UCC), Armagan Tarim (UCC), Fiona Kiely (Marymount Hospice Cork)

WirelessTouch

Supporting independent living for people with epilepsy

Challenge Due to privacy concerns, video-based smart-home monitoring and auto-logging systems cannot always be applied despite being the most accurate. There is a need to develop new high-performance approaches that preserve privacy for a range of applications that support independent living.  

Solution The WirelessTouch team proposes to use 3D-wireless sensor technology to enable real-time measurement with a higher degree of privacy than conventional video-based monitoring. 

Team Lina Xu (UCD), Quan Le (UCD), Edel Curran (Epilepsy Ireland) 

UCD SPHERE

Reducing the burden of preeclampsia

Challenge Preeclampsia is extremely difficult to diagnose and kills 50,000 mothers and 500,000 babies every year. We propose to develop a new test that will help us save the lives of mothers and babies.  

Solution Combining the power of machine learning, and cutting-edge omics methodologies, we will develop a new platform for the diagnosis and treatment of preeclampsia. This will be an affordable tool to closely observe pregnancies complicated by preeclampsia and prevent unnecessary adverse outcomes for both mother and baby. 

Team Patricia Maguire (UCD), Fionnuala Ní Áinle (UCD), Mary Higgins (National Maternity Hospital) 

https://ucdconwaysphere.wordpress.com/

REEP

Reduce electronic waste generation by empowering people to repair, reuse and refurbish electrical and electronic equipment

Challenge The societal impact of citizen-driven initiatives aimed at enabling the repair and reuse of electrical and electronic products is currently limited by a lack of access to relevant information and spare components.  

Solution The REEP team proposes to empower people to repair, reuse and refurbish electrical and electronic equipment by building an online marketplace that uses AI to meet the needs of reuse facilities, repair communities and citizens.  

Team Mathieu d'Aquin (NUIG), Umair Ul Hassan (NUIG), Vincent Carragher (Galway Waste Coop)