Road Anomaly Detection with Group Intelligence Perception

we consider a collection of the actual combat training of the troops that continues to deepen, and the use of training vehicles is becoming more frequent. We study the problem of detecting abnormal road surface, which may lead to traffic safety accidents and damage to the troops and officers and soldiers. In order to grasp the road situation in time, we design a road quality monitoring system based on group intelligence perception. The system adopts the concept of group intelligence perception, develops the data acquisition software under the smartphone Android environment, and places the mobile phone as the sensing terminal in the vehicle, collects the acceleration, speed, latitude and longitude data generated during the driving process of the vehicle, and collects the collected data. We establish the SVM support vector machine and processing application layer in detecting anomalies, further, we perform the experiments of system on the actual road environment, which can automatically detect the road anomaly.