Pav Analytics

AI-based pavement condition assessment for cycling and walking infrastructure

Pav Analytics

Overview

Pav Analytics is an AI-based pavement condition assessment system focused on improving walking and cycling infrastructure. The project integrates intelligent sensing, data analytics, and visualization tools to support infrastructure maintenance and planning.

Funding

  • EU Commission RRF (Grant Number 22/NCF/OT/11220)
  • Insight Research Ireland (Grant Number 12/RC/2289_P2)

Duration

July 2023 – March 2025

Team

  • PI: Dr Ihsan Ullah
  • Co-PI: Dr Waqar Shahid Qureshi

Researchers:

  • Syed M Haider Shah
  • Muhammad Hassam Baig
  • Jeziel Antonio Ayala Garcia

Collaborators

  • Kathleen Belbonjean (Societal Impact Champion, GortCycleTrail)
  • Gerard O’Dea (Asset Management Officer, TII)
  • David Power

Description

The project develops an intelligent sensing and analytics platform for assessing pavement conditions.

  • Sensors mounted on bicycles collect pavement data
  • Data is processed using AI and computer vision techniques
  • Outputs are visualized through a software suite
  • Generates standardized pavement condition ratings (PSCI)
  • Supports stakeholder-driven refinement
  • Enables citizen participation for reporting issues

Thematic Areas

  • Artificial Intelligence / Machine Learning
  • Computer Vision & Robotics
  • Smart Infrastructure
  • Health

Impact (UN SDGs)

  • SDG 3: Health and Wellbeing
  • SDG 9: Industry, Innovation & Infrastructure
  • SDG 11: Sustainable Cities & Communities
  • SDG 13: Climate Action