The Impact of Data Quality in the Context of Pedestrian Movement Analysis

Abstract

AbstractPositioning data sets gathered from GPS recordings of moving people or vehicles and usage logs of telecommunications networks are being increasingly used as a proxy to capture the mobility of people in a variety of places. The purpose of use of these data sets is wide-ranging and requires the development of techniques for collaborative map construction, the analysis and modelling of human behaviour, and the provision of context- aware services and applications. However, the quality of these data sets is affected by several factors depending on the technology used to collect the position and on the particular scenario where it is collected. This paper aims at assessing the quality and suitability of GPS recordings used in analysing pedestrian movement in two different recreational applications. Therefore, we look at two positioning data sets collected by two distinct groups of pedestrians, and analyse their collective movement patterns in the applications of a mobile outdoor gaming and as well as a park recreational usage. Among other findings, we show that the different reading rates of the pedestrians’ position lead to different levels of inaccuracy in the variables derived from it (e.g. velocity and bearing). This was significant in the case of bearing values that were calculated from GPS readings which, in turn, has shown a strong impact on the size of clusters of movement patterns.KeywordsPattern MiningCore PointTrajectory PatternNoise PointPedestrian MovementThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.