This paper presents a fusion method for combining outputs acquired by low-cost inertial measurement units and electronic magnetic compasses. Specifically, measurements of inertial accelerometer and gyroscope sensors are combined with no-inertial magnetometer sensor measurements to provide the optimal three-dimensional (3D) orientation of the sensors’ axis systems in real time. The method combines Euler–Cardan angles and rotation matrix for attitude and heading representation estimation and deals with the “gimbal lock” problem. The mathematical formulation of the method is based on Kalman filter and takes into account the computational cost required for operation on mobile devices as well as the characteristics of the low-cost microelectromechanical sensors. The method was implemented, debugged, and evaluated in a desktop software utility by using a low-cost sensor system, and it was tested in an augmented reality application on an Android mobile device, while its efficiency was evaluated experimentally.

This paper presents a methodology and its software implementation for the performance evaluation of low-cost accelerometer and magnetometer sensors for use in geomatics applications. A known mathematical calibration model has been adopted. The method was completed with statistical methodologies for adjusting observations and has been extended to calculate accuracies for the attitude, heading, and tilt angles estimation that are of interest to geomatics applications. The evaluation method consists of two stages. First, the evaluation method reviews the total magnitude of acceleration or the strength of the magnetic field. Second, the evaluation is more detailed and concerns the determination of mathematical parameters that describe both accelerometer and magnetometer working model. A software tool that implements the evaluation model has been developed and is applied both in accelerometer and magnetometer measurement data-sets acquired from a low-cost sensor system.

In this paper, a procedure for calibrating the image sensors of mobile devices and evaluating their results was developed and implemented in a software application. Regarding the calibration, two methods were used, an OpenCV function and a photogrammetry method, which used the same camera model. In evaluating the calibration results, a method is proposed that uses single-image rectification to examine the performance of the calibration parameters in a practical and supervisory way. After an experiment followed by a study, a standard is proposed regarding the number and shooting angles of the photographs that should be used in the calibration. During the development, problems related to processing large images and automating processes were solved. Finally, the procedure and software application were tested in a case study.

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The work described concerns the first major study on heavy goods vehicles operating on the trans-European links in Greek territory. The study period coincides with a period in which major development in the national road network took place that required the support by specific studies concerning pavement design, road management, and toll collection. Data were collected at seven specific sites on the main axes of the main national roads. A total of about 3,053,116 records at all sites were collected concerning all vehicle categories. Data were collected using permanent weigh-in-motion (WIM) instrumentation with either rigid or flexible sensors. In addition, comparison measurements were taken from high-speed and low-speed WIM systems to examine the validity of the above systems to be used in law enforcement for overloaded vehicles. Analysis of the data revealed that the initial sets included a series of counts that were not reliable. False data were detected by imposing various physical or technical filters. The consistency of the remaining good-quality data was examined by using simple analysis techniques. In the final stage of the work much emphasis was given in the development of a comprehensive database of WIM measurements. This database is unique for the Greek national road network and is a necessary step in order to provide useful information and support future actions in the area of pavement design and maintenance.