Monitoramento da qualidade da pavimentação de vias utilizando computação em nuvem veicular

Abstract

Defects in street surfaces, such as potholes and imperfections, can occur at any time, depending on the conditions and life of the road. These imperfections on street surfaces can compromise traffic safety and also cause premature wear of vehicle parts. In this work, we propose an architectural model for the Vehicular Cloud Computing environment, capable of monitoring and evaluating the quality of street roughness, using the International Roughness Index (IRI) metric. The objective of this work is to develop an automated architectural model of road roughness monitoring to measure pavement roughness based on the vibrational response using smartphone sensors. To inform drivers about the quality of paving of the lanes on a given route, so that the driver can choose a more comfortable and safer route. For the experiments, we developed an application android, to record the roughness quality of the roads, together with a web service that we also developed, to store the data generated by the application. The experiments were carried out in the city of Garanhuns-PE, covering stretches at a speed of 50 km/h, using three android cell phones positioned on top of the car’s dashboard. The car model used was a Volkswagen Fox 1.0. The results affirm that our architectural model can monitor, measure and display on the map the quality of road roughness. In the application, the places where the IRI records were made are plotted on the map.