Development and Validation of a Smartphone-Based IRI Detection Framework: A Rural Road Case Study in Egypt

Real-time detection of pavement roughness (PR) is essential to any effective pavement management system (PMS). Traditional methods for assessing the International Roughness Index (IRI) are expensive, time-consuming, and cause several challenges for transportation agencies in developing countries as Egypt. This study establishes a comprehensive framework for collecting and analyzing data from the three-axis accelerometer embedded in modern smartphones to estimate real-time IRI. This approach utilizes vehicle vibration data and vertical acceleration signals, combined with GPS coordinates from the smartphone. A calibration step was conducted to optimize sensor sensitivity and signal filtering processes, ensuring accuracy. The proposed framework integrates speed variation, calibration, and statistical analysis in accordance with ASTM standards to confirm accuracy and repeatability. Results show a high degree of precision with a maximum coefficient of variation (CV) of 11% between repeated runs, with a minimum accuracy of 92% for detecting pavement roughness. Then, the framework was tested on a 160-kilometer rural freeway in Egypt.