Monitoring road surface anomalies towards dynamic road mapping for future smart cities

The development of Smart Cities aims to transform city infrastructures and services through the use of information and communication technologies. One aspect of Smart City applications is the demand for more efficient and safe transportation systems. Specifically, road anomalies are some of the challenges that contribute to the increase in vehicle damage and decrease in driver safety. In this paper, we propose a road surface condition monitoring system that utilizes low cost MEMS acceleration sensors and GPS receivers within a tablet to detect and localize road surface anomalies. Several types of road information data were collected, analyzed, and processed using statistical and time domain analysis for feature extraction of the various events. We also propose a multi-level decision-tree classifier to precisely distinguish between the events. In addition, the use of the tablet sensors to localize the monitored events is discussed.