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Künstliche Intelligenz 26(3) - August 2012

https://dl.gi.de/handle/20.500.12116/11104
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Auflistung Künstliche Intelligenz 26(3) - August 2012 nach Autor:in "Giannotti, Fosca"

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  • Zeitschriftenartikel
    Data Science for Simulating the Era of Electric Vehicles
    (KI - Künstliche Intelligenz: Vol. 26, No. 3, 2012) Janssens, Davy; Giannotti, Fosca; Nanni, Mirco; Pedreschi, Dino; Rinzivillo, Salvatore
    The vision and scientific challenges presented in this paper are the objectives of the FET-FP7 project DATASIM. The project aims at providing an entirely new and highly detailed spatio-temporal microsimulation methodology for human mobility, grounded on massive amounts of big data of various types and from various sources, with the goal to forecast the nation-wide consequences of a massive switch to electric vehicles, given the intertwined nature of mobility and power distribution networks.
  • Zeitschriftenartikel
    Discovering the Geographical Borders of Human Mobility
    (KI - Künstliche Intelligenz: Vol. 26, No. 3, 2012) Rinzivillo, Salvatore; Mainardi, Simone; Pezzoni, Fabio; Coscia, Michele; Pedreschi, Dino; Giannotti, Fosca
    The availability of massive network and mobility data from diverse domains has fostered the analysis of human behavior and interactions. Broad, extensive, and multidisciplinary research has been devoted to the extraction of non-trivial knowledge from this novel form of data. We propose a general method to determine the influence of social and mobility behavior over a specific geographical area in order to evaluate to what extent the current administrative borders represent the real basin of human movement. We build a network representation of human movement starting with vehicle GPS tracks and extract relevant clusters, which are then mapped back onto the territory, finding a good match with the existing administrative borders. The novelty of our approach is the focus on a detailed spatial resolution, we map emerging borders in terms of individual municipalities, rather than macro regional or national areas. We present a series of experiments to illustrate and evaluate the effectiveness of our approach.