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Saving Human Lives: What Complexity Science and Information Systems can Contribute.

Helbing D, Brockmann D, Chadefaux T, Donnay K, Blanke U, Woolley-Meza O, Moussaid M, Johansson A, Krause J, Schutte S, Perc M - J Stat Phys (2014)

Bottom Line: We discuss models and data of crowd disasters, crime, terrorism, war and disease spreading to show that conventional recipes, such as deterrence strategies, are often not effective and sufficient to contain them.Many common approaches do not provide a good picture of the actual system behavior, because they neglect feedback loops, instabilities and cascade effects.We highlight that a suitable system design and management can help to stop undesirable cascade effects and to enable favorable kinds of self-organization in the system.

View Article: PubMed Central - PubMed

Affiliation: ETH Zurich, Swiss Federal Institute of Technology, 8092 Zurich, Switzerland ; Risk Center, ETH Zurich, Swiss Federal Institute of Technology, 8092  Zurich, Switzerland.

ABSTRACT

We discuss models and data of crowd disasters, crime, terrorism, war and disease spreading to show that conventional recipes, such as deterrence strategies, are often not effective and sufficient to contain them. Many common approaches do not provide a good picture of the actual system behavior, because they neglect feedback loops, instabilities and cascade effects. The complex and often counter-intuitive behavior of social systems and their macro-level collective dynamics can be better understood by means of complexity science. We highlight that a suitable system design and management can help to stop undesirable cascade effects and to enable favorable kinds of self-organization in the system. In such a way, complexity science can help to save human lives.

No MeSH data available.


Example of a festival site for the case of the “Zürifäscht” in Zürich, Switzerland, showing the perimeter (red) and the stage layout. The main train transportation hubs are indicated by green circles (Color figure online)
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Fig4: Example of a festival site for the case of the “Zürifäscht” in Zürich, Switzerland, showing the perimeter (red) and the stage layout. The main train transportation hubs are indicated by green circles (Color figure online)

Mentions: Here, we demonstrate the potential of location-data obtained from mobile phones during the Züri Fäscht festival 2013 in Switzerland (see Fig. 4). The Züri Fäscht is a three-days event comprising an extensive program with concerts, dance parties, and shows. It is hosted in the city center of Zürich and is the biggest festival in Switzerland. Up to 2 million visitors have been estimated to attend the festival over the course of three days. In 2013, 56,000 visitors downloaded the festival app, from which 28,000 gave informed consent to anonymously contributed their location data. Figure 5 shows the number of users simultaneously contributing their location data over the course of the event, and the amount of data samples collected. While collecting only a subsample from the entire crowd, previous work [36] showed a correlation coefficient greater than between the estimated density and actual density determined from video recordings.Fig. 4


Saving Human Lives: What Complexity Science and Information Systems can Contribute.

Helbing D, Brockmann D, Chadefaux T, Donnay K, Blanke U, Woolley-Meza O, Moussaid M, Johansson A, Krause J, Schutte S, Perc M - J Stat Phys (2014)

Example of a festival site for the case of the “Zürifäscht” in Zürich, Switzerland, showing the perimeter (red) and the stage layout. The main train transportation hubs are indicated by green circles (Color figure online)
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4457089&req=5

Fig4: Example of a festival site for the case of the “Zürifäscht” in Zürich, Switzerland, showing the perimeter (red) and the stage layout. The main train transportation hubs are indicated by green circles (Color figure online)
Mentions: Here, we demonstrate the potential of location-data obtained from mobile phones during the Züri Fäscht festival 2013 in Switzerland (see Fig. 4). The Züri Fäscht is a three-days event comprising an extensive program with concerts, dance parties, and shows. It is hosted in the city center of Zürich and is the biggest festival in Switzerland. Up to 2 million visitors have been estimated to attend the festival over the course of three days. In 2013, 56,000 visitors downloaded the festival app, from which 28,000 gave informed consent to anonymously contributed their location data. Figure 5 shows the number of users simultaneously contributing their location data over the course of the event, and the amount of data samples collected. While collecting only a subsample from the entire crowd, previous work [36] showed a correlation coefficient greater than between the estimated density and actual density determined from video recordings.Fig. 4

Bottom Line: We discuss models and data of crowd disasters, crime, terrorism, war and disease spreading to show that conventional recipes, such as deterrence strategies, are often not effective and sufficient to contain them.Many common approaches do not provide a good picture of the actual system behavior, because they neglect feedback loops, instabilities and cascade effects.We highlight that a suitable system design and management can help to stop undesirable cascade effects and to enable favorable kinds of self-organization in the system.

View Article: PubMed Central - PubMed

Affiliation: ETH Zurich, Swiss Federal Institute of Technology, 8092 Zurich, Switzerland ; Risk Center, ETH Zurich, Swiss Federal Institute of Technology, 8092  Zurich, Switzerland.

ABSTRACT

We discuss models and data of crowd disasters, crime, terrorism, war and disease spreading to show that conventional recipes, such as deterrence strategies, are often not effective and sufficient to contain them. Many common approaches do not provide a good picture of the actual system behavior, because they neglect feedback loops, instabilities and cascade effects. The complex and often counter-intuitive behavior of social systems and their macro-level collective dynamics can be better understood by means of complexity science. We highlight that a suitable system design and management can help to stop undesirable cascade effects and to enable favorable kinds of self-organization in the system. In such a way, complexity science can help to save human lives.

No MeSH data available.