Street Surface Quality Assessment and Visualization using Gyro Sensor

Street maintenance is one of important tasks for transportation safety. An inclusive report is required for demonstrating the quality of street surface in order to have a precise plan for repairing any defects on street at the right locations. Most observations from any government agencies are usually done by human, however reports about street surface are not well-appointed enough due to the limitation of human cognition and documentation. This paper addresses the according issue by using computation process that uses the power of the Internet of Things (IoT) to analyze the movement of gyro data with locations and time along driving routes, and then generates a visualization report to point out any broken street surface. It has been found that the analysis of gyro data using linear regression could enable street surface quality assessment and visualization for improving road safety.