Pav-Analytics: Intelligent Sensing System for Greenways and Cycleways
- Challenge:OurTech Challenge
- Co-Funders:European Union
- Phase:Seed
- Team Lead:Dr Ihsan Ullah, University of Galway
- Team Co-Lead:Dr Waqar Shahid Qureshi, TU Dublin
- Societal Impact Champion:Katleen Bell-Bonjean, Gort Cycle Trails
Funders
Funded by: European Union & Government of Ireland
1. Cycle routes and greenways should meet satisfactory standards of width, gradient, and surface condition, to provide a user-friendly and low-risk experience for all abilities.
2. Pavement condition rating indices, such as the Pavement Surface Condition Index (PSCI), play a crucial role in assessing and rating the condition of pavements across Ireland, but manual surveys are time-consuming and tedious.
3. 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.
4. The lack of a smart system for data sensing and collection based on the quality criteria mentioned in the National Cycle Manual presents a challenge in Ireland, hindering informed and citizen-induced planning by local authorities.
5. A reliable framework for data analysis and visualization is crucial to effectively address the maintenance and improvement of cycle and walking paths, supporting sustainable and active transport efforts at a broader European and international level.
1. Our solution develops an intelligent sensing system for data collection on cycle routes and greenways.
2. We create reliable data analysis and visualization software for standard pavement condition ratings.
3. Stakeholder engagement and collaboration drive the development of a modified PSCI rating system.
4. Our cost-effective and privacy-preserving approach improves maintenance decision-making for cycle and footpaths.