Two Trinity Engineering Projects Secure SEAI RD&D Funding

The funding programme objectives are clearly set out to: 

• Support solutions that enable technical and other barriers to market uptake to be overcome 

• Grow Ireland's national capacity to access, develop and apply international class RD&D 

• Provide guidance and support to policy makers and public bodies 

• Accelerate competitive energy-related products, processes and systems 

The projects are outlined below, plan to advance Ireland’s move towards a cleaner and more secure energy system. 

CIRCUIT: Causal Inference for Resilient Cities and Urban Integrated Transport 

Professor Brian Caulfield has been awarded €1 million to lead the CIRCUIT project, which will examine how transport and energy use shape environmental impacts in Ireland’s cities. 

The CIRCUIT project focuses on understanding the environmental impact of transport and energy use in Ireland. Transport accounts for about 19% of total emissions, while residential use and energy industries contribute 10% and 16%, respectively. To manage these impacts, we need to understand the connections between city growth, transportation systems, and energy consumption. The CIRCUIT project will use advanced statistical and machine learning techniques to analyse travel behaviour and energy use patterns. 

Speaking about the project, Professor Caulfield said: 

“This four year project will examine the technical and systemic barriers to sustainable mobility by capturing emerging trends such as electric micro mobility, shifting travel patterns, and clean energy transitions. Through causal inference techniques, CIRCUIT will disentangle complex behavioural, spatial, and temporal interactions between energy use and mobility. This will support targeted interventions that promote energy efficient, resilient, and inclusive urban environments.” 

DISCLOSE: Distributed Sensing and Collaborative Optimisation for Smart Energy efficient Buildings 

Led by Trinity College Dublin, Project DISCLOSE aims to create an automated, intelligent energy management framework that allows everyday household devices to independently monitor and optimise their electricity usage. Currently, homeowners looking to benefit from smart metering and time-of-day billing must either manually schedule their appliance usage or invest in expensive, centralised systems that require extensive retrofits and raise significant data privacy concerns.

DISCLOSE directly addresses these challenges by developing a localised automation system where devices can securely coordinate their energy consumption without ever sharing personal data with external energy providers or grid operators. Ultimately, this privacy-preserving approach aims to help consumers seamlessly lower their energy bills, improve the resilience of the national electric grid, and encourage a wider transition to sustainable, energy-efficient homes.  

Speaking about the project, Dr. Shanker, Principal Investigator of DISCLOSE said:  

"In this project, we are moving away from traditional, centralised home energy management towards a distributed consensus model. By leveraging novel lightweight consensus algorithms and flexible smart contracts, connected devices will be able to securely aggregate consumption data and collaboratively determine optimal control schedules in real-time. At the same time, the system will retain the flexibility to adapt to human-driven interactions and overrides automatically. For smart home system design, this means we can deploy granular, automated demand-side management using the existing computational capabilities of modern devices over standard wireless interfaces. This effectively eliminates the need for expensive hardware retrofits or reliance on subscription-based cloud analytics, fundamentally democratising how buildings handle active load management."