Contributo in atti di convegno, 2018, ENG, 10.1109/DSAA.2018.00061
Ferretti M.; Barlacchi G.; Pappalardo L.; Lucchini L.; Lepri B.
Department of Geography, King's College London, London, UK; Department of Information Engineering and Computer Science, University of Trento and Fondazione Bruno Kessler, Trento, Italy; CNR-ISTI, Pisa, Italy; Department of Information Engineering and Computer Science, University of Trento and Fondazione Bruno Kessler, Trento, Italy; Fondazione Bruno Kessler, Trento, Italy
The availability of massive data-sets describing human mobility offers the possibility to design simulation tools to monitor and improve the resilience of transport systems in response to traumatic events such as natural and man-made disasters (e.g., floods, terrorist attacks, etc...). In this perspective we propose ACHILLES, an application to models people's movements in a given transport mode through a multiplex network representation based on mobility data. ACHILLES is a web-based application which provides an easy-to-use interface to explore the mobility fluxes and the connectivity of every urban zone in a city, as well as to visualize changes in the transport system resulting from the addition or removal of transport modes, urban zones and single stops. Notably, our application allows the user to assess the overall resilience of the transport network by identifying its weakest node, i.e. Urban Achilles Heel, with reference to the ancient Greek mythology. To demonstrate the impact of ACHILLES for humanitarian aid we consider its application to a real-world scenario by exploring human mobility in Singapore in response to flood prevention.
DSAA 2018 - IEEE 5th International Conference on Data Science and Advanced Analytics, pp. 472–480, 01-04 October 2018
Urban science, Data science, Human mobility, Complex systems, Network science, Multiplex networks, Resilience, Social good
ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"
ID: 404566
Year: 2018
Type: Contributo in atti di convegno
Creation: 2019-07-15 14:32:30.000
Last update: 2020-10-26 15:22:46.000
CNR authors
External IDs
CNR OAI-PMH: oai:it.cnr:prodotti:404566
DOI: 10.1109/DSAA.2018.00061
ISI Web of Science (WOS): 000459238600052
Scopus: 2-s2.0-85062826455