Real-time and post processing of GPS data in the field of visualizing asphalt paving operations

Utilization of global positioning system (GPS) to analyze the movements of machinery during the asphalt paving process is a growing practice. However, the accuracy of GPS measurements is affected by a number of factors that lead to noise in the GPS data. Due to these missing accuracy in the GPS data the asphalt paving professionals have problems interpreting and using the data in their operational context. Therefore, a lot would be gained if the noise in the GPS data could be filtered so asphalt paving operations could be analyzed and improved in greater detail. Filtering, however, is a difficult task. The movements of machinery in asphalt paving are very machine-specific and a high level of detail is required to analyze their operations. For example: Whether a certain pattern in the GPS data is caused by noise or by the machine-specific movement is not easily recognisable. This paper will explore and investigate problems with filtering GPS data and will do so for post-processing as well as for real-time processing. In particular, we analyze two post-processing smoothing techniques for roller GPS data and one realtime processing technique for a paver GPS data. The data were recently gathered on an actual paving project. Smoothing the GPS data will be a crucial step for realistic visualization of movements of machinery at the construction site. Such visuals are vital for operators and decision makers to map, understand, and improve their operational strategies and behaviour.