An Application of Android Sensors and Google Earth in Pavement Maintenance Management Systems for Developing Countries

Abstract

Governments and road agencies face the challenging task of maintaining roads. One of the reasons this is challenging is that the maintenance process requires utilizing a substantial amount of road network condition data. There are many approaches for measuring road surface conditions which are very costly and time-consuming, as well as requiring skillful operators. Developing countries have limited budgets for planning and monitoring road maintenance. This research aims to establish a low-cost pavement maintenance management system for intermediate and small cities in developing countries. The system utilizes low-cost sensors embedded in smartphones that can be used to measure road surface conditions. Google Earth is then used to present maintenance data, select ‏a maintenance ‏strategy, and view the maintenance output information. Road Lab Pro, an android application, is used to collect the data and estimate the surface condition of roads by using accelerometers, gyroscopes‏, and a GPS. The road network is divided ‏into segments and the road surface conditions are estimated for each segment using the smartphone application and a suspension vehicle. The required maintenance activities for these segments are then established. A priority index is determined for each segment to decide which segments should be maintained with the available budget. This effort allows us to investigate the feasibility of assessing road surface roughness using a smartphone to determine the presence of road distresses and the overall road condition, which is taken into account when making maintenance decisions. The application of this system reveals that these new technologies can provide cost-effective, easy-handling, and efficient ways for a road agency to perform good maintenance planning.

Impact of Landscape Factors on Automobile Road Deformation Patterns—A Case Study of the Almaty Mountain Road

“…An Internet-of-Things approach was suggested that used sensors in the pavement which indicated its state in real time [7]. Low-cost methodologies and indicators installed on smartphones are applied for road diagnostics in developing countries [8]. Most of these approaches cannot be implemented in the republic of Kazakhstan, as there is lack of both financial and human resources for detailed field diagnostics of huge lengths of road.…”