Smart Traffic Signs Retroreflectivity Monitoring System Islamabad

This research presents an integrated framework combining a systematic literature review, a Random Forest machine learning algorithm, and a citizen-centric mobile application to monitor traffic sign retroreflectivity degradation in Islamabad. The model predicts sign degradation with 91.2% accuracy, while the mobile app reduces reporting time by 60% through automated assessment and complaint submission to municipal authorities. The study offers a scalable, smart urban road safety solution for tropical climates, particularly in South Asian cities like Islamabad.