Now showing 1 - 8 of 8
  • Publication
    Constructing semantic interpretation of routine and anomalous mobility behaviors from big data
    ( 2015) ; ; ;
    Andrienko, Natalia
    ;
    Andrienko, Gennady
    Annually organized VAST Challenges provide a unique opportunity to analyze complex data with available ground truth. In 2014, one of the tasks was to interpret routine and anomalous patterns of human mobility based on big data: trajectories of cars and credit card transactions. We describe a scalable visual analytics approach to solving this problem. Repeatedly visited personal and public places were extracted from trajectories by finding spatial clusters of stop points. Temporal patterns of peoples presence in the places resulted from spatio-temporal aggregation of the data by the places and hourly intervals within the weekly cycle. Based on these patterns, we identified the meanings or purposes of the places: home, work, breakfast, lunch and dinner, etc. Meanings of some places could be refined using the credit card transaction data. By representing the place meanings as points on a 2D plane, we built an abstract semantic space and transformed the original trajectories to trajectories in the semantic space, i.e., performed semantic abstraction of the data. Spatio-temporal aggregation of the transformed trajectories into flows between the semantic places and subsequent clustering of time intervals by the similarity of the flow situations allowed us to reveal and analyze the routine movement behaviors. To detect anomalies, we (a) investigated the visits to the places with unknown meanings, and (b) looked for unusual presence times or visit durations at different semantic places. The analysis is scalable since all tools and methods can be applied to much larger data. Moreover, the semantic data abstraction can serve as a tool for protecting the personal privacy.
  • Publication
    Using Bluetooth to track mobility patterns: Depicting its potential based on various case studies
    ( 2013)
    Ellersiek, Timothy
    ;
    Andrienko, Gennady
    ;
    Andrienko, Natalia
    ;
    ; ;
    Müller, Marc
    During the past years the interest in the exploitation of mobility information has increased significantly. A growing number of companies and research institutions are interested in the analysis of mobility data with demand of a high level of spatial detail. Means of tracking persons in our environment can nowadays be fulfilled by utilizing several technologies, for example the Bluetooth technology, offering means to obtain movement data. This paper gives an overview of four case studies in the field of Bluetooth tracking which were conducted in order to provide helpful insights on movement aspects for decision makers in their specific microcosm. Aim is to analyse spatio-temporal validity of Bluetooth tracking, and in doing so, to describe the potential of Bluetooth in pedestrian mobility mining.
  • Publication
    Visual analytics for understanding spatial situations from episodic movement data
    ( 2012)
    Andrienko, Natalia
    ;
    Andrienko, Gennady
    ;
    ; ;
    Continuing advances in modern data acquisition techniques result in rapidly growing amounts of georeferenced data about moving objects and in emergence of new data types.We define episodic movement data as a new complex data type to be considered in the research fields relevant to data analysis. In episodic movement data, position measurements may be separated by large time gaps, in which the positions of the moving objects are unknown and cannot be reliably reconstructed. Many of the existing methods for movement analysis are designed for data with fine temporal resolution and cannot be applied to discontinuous trajectories. We present an approach utilising Visual Analytics methods to explore and understand the temporal variation of spatial situations derived from episodic movement data b y means of spatio-temporal aggregation. The situations are defined in terms of the presence of moving objects in different places and in terms of flows (collective movements) between the places. The approach, which combines interactive visual displays with clustering of the spatial situations, is presented by example of a real dataset collected by Bluetooth sensors.
  • Publication
    Analytical workflow of monitoring human mobility in big event settings using bluetooth
    ( 2011) ; ; ;
    Andrienko, Gennady
    ;
    Andrienko, Natalia
    In recent times, consumer research at major social events received significant interest by organizing companies. Understanding the movements and motivations of the customers enables new business strategies and is needed to minimize the risk of investment. The spatiotemporal complexity of major events poses high demands on survey and analytical methods. New technological advances in both event monitoring systems and evaluation methods of movement data provide new insights into the behavioral patterns of customers by preserving their privacy. In this paper we present a work that seeks to systematize the research process of design, collection, and analysis of visitor behavior in a mixed indoor-outdoor event setting using Bluetooth sensor technology. The defined workow is comprised of 5 steps and designed to answer heterogeneous business questions with respect to customer movement behavior in a single event context. Our approach is applied in a real-world business applicati on for a Formula 1 event.
  • Publication
    Modeling micro-movement variability in mobility studies
    During the past years the interest in the exploitation of mobility information has increased significantly. Along with these interests, new demands on mobility data sets have been posed. One particular demand is the evaluation of movement data on a high level of spatial detail. The high dimensionality of geographic space, however, makes this requirement hard to fulfill. Even large mobility studies cannot guarantee to comprise all movement variation on a high level of detail. In this paper we present an approach to increase the variability of movement data on microscopic scale in order to achieve a better representation of population movement. Our approach consists of two steps. First, we perform a spatial aggregation of trajectory data in order to counteract sparseness and to preserve movement on macroscopic scale. Second, we disaggregate the data in geographic space based on traffic distribution knowledge using repeated simulation. Our approach is applied in a real-world business application for the Ger-man outdoor advertising industry to measure the performance of poster sites.
  • Publication
    Spatial data mining in practice
    Almost any data can be referenced in geographic space. Such data permit advanced analyses that utilize the position and relationships of objects in space as well as geographic background information. Even though spatial data mining is still a young research discipline, in the past years research advances have shown that the particular challenges of spatial data can be mastered and that the technology is ready for practical application when spatial aspects are treated as an integrated part of data mining and model building. In this chapter in particular, we give a detailed description of several customer projects that we have carried out and which all involve customized data mining solutions for business relevant tasks. The applications range from customer segmentation to the prediction of traffic frequencies and the analysis of GPS trajectories. They have been selected to demonstrate key challenges, to provide advanced solutions and to arouse further research questions.
  • Publication
    Sample bias due to missing data in mobility surveys
    A growing number of companies use mobility information in their day-to-day business. One requirement thereby is that inference about population-wide mobility patterns can be made. Therefore, it is not only important to find mobility patterns in a given data sample but also to assert their validity for the total population. This aspect of analysis has been largely neglected in mobility data mining research, which limits the applicability of the whole algorithmic field. In this paper we will analyze one aspect of sample bias due to incomplete mobility data. We will provide a systematic approach to detect dependencies between mobility behavior, socio-demography and missing data. Further, we apply the approach to a large GPS mobility survey in Switzerland and show that our concerns are justified and require attention in future research. We hope that our paper will raise the awareness that representativity of mobile behavior cannot be taken for granted in mobility surveys du e to missing data and is a research direction of utmost importance.
  • Publication
    A general pedestrian movement model for the evaluation of mixed indoor-outdoor poster campaigns
    Over the last few years new measurement technology has revolutionized the performance measurement in outdoor advertising. A handful of pioneer countries trace personal mobility now via GPS devices, which allows for precise performance results of arbitrarily positioned outdoor poster campaigns. However, GPS technology has the drawback that it cannot be applied indoors due to signal loss. In Switzerland and Germany many valuable posters are situated in public buildings such as train stations or shopping malls and their evaluation is of high interest. In this paper we therefore present a new approach for the evaluation of mixed indoor-outdoor campaigns. Our approach consists of a general pedestrian movement model in restricted spaces which can be integrated into standard trajectory evaluation. Our approach has been implemented for 27 major train stations in Switzerland.