As Ireland’s cycling infrastructure grows it is vital that cycle routes and greenways, just like roads, are safe for users. Each route should meet minimum standards of width, gradient and surface condition.
The unique pavement characteristics of cycle routes and greenways, such as the Dublin-Galway Greenway, pose challenges for conventional data collection methods using Road Survey Profile (RSP) vehicles, leading to inaccuracies in pavement condition data. Manual surveys are time-consuming and tedious. Furthermore, currently the maintenance of active travel routes, greenways, or urban cycle tracks are based on reactive approach i.e. waiting until the damage becomes severe before repairs are made. This often results in higher repair costs, increased risks for cyclists and pedestrians, and a reduction in overall infrastructure lifespan.
Recognising this acute need, a team led by Dr Ihsan Ullah of the Insight SFI Research Centre for Data Analytics at University of Galway created
Pav-Analytics – an intelligent sensing system for cost-effective data collection and analysis using advanced sensors mounted on mobile units.
Pav-Analytics aims to shift from this reactive approach to a proactive and predictive maintenance model, using real-time data to identify potential hazards before they worsen. This ensures more efficient use of resources and improves the safety and usability of cycling infrastructure.
A reliable framework for data collection, analysis, and visualisation is critical which will help in not only maintaining and improving infrastructure, but also will help in improving health and wellbeing of the citizens and reduction of carbon emission. Hence supporting United Nation Sustainable development goals 3 (health and Wellbeing), 11 (sustainable cities and communities), and 13 (Climate action), as well as Government of Ireland Sustainable Mobility Policy.
Dr Ullah is working with Dr Waqar Shahid Qureshi of from the School of Computer Science University of Galway (previously was in TU Dublin) to create a cost-effective and privacy-preserving approach to improving maintenance decision-making for cycle and footpaths.
The project promises to create a smart decision support framework that utilise AI to provide automated cycle route surface condition assessment. The framework uses low-cost cameras and sensors mounted on bicycles to capture data for the condition of cycle paths and greenways. The data will then be processed on an AI-based software on the cloud to rate segments of the cycle track based on their visual distress, ride roughness, vegetations and drainage gradient.
This information will then provide digital maps of surface condition and visual distresses of different offline and inline cycle tracks in Ireland. The digital maps will be integrated into the decision support framework to report segments of cycle tracks that require a specific treatment to fix the segment for a safer travel, ensuring they are safe and accessible for everyone.
The project’s innovative framework supports SDG 13 (Climate Action) by encouraging more sustainable forms of transportation. By promoting cycling and walking through well-maintained paths, Pav-Analytics contributes to the reduction of carbon emissions, aligns with Ireland’s Sustainable Mobility Policy, and helps to meet the nation’s climate goals. Safer and more accessible paths motivate more people to choose cycling as an alternative to car travel, reducing traffic congestion and air pollution in urban areas.
The multidisciplinary team, including co-lead Dr. Waqar Shahid Qureshi (another Lecturer in the School of Computer Science (previously postdoc in TU Dublin) , Pav-Analytics brings together expertise in data analytics, AI, Robotics and Sensing and pavement engineering. This collaboration ensures that the project is not only technically sound but also practical for real-world applications. The digital maps created by the system will help local authorities make data-driven decisions on where to allocate maintenance resources, ensuring a safer, greener and more efficient active travel network across Ireland.
This timely project has been recognised and supported by SFI and the Government of Ireland through the
OurTech Challenge Fund, part of the National Challenge Fund.
The OurTech Challenge Fund gives researchers the opportunity to explore how digital technologies could enhance government processes and functions. Following review of applications, successful teams receive funding of up to €200,000 and training to accelerate development of their idea. A number of teams will be selected as finalists and receive up to €500,000 to further develop their idea before an overall winner is selected for the €1 million prize award.
Katleen Bell-Bonjean of Gort Cycle Trails is Societal Impact Champion for Pav-Analytics.
