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A Stigmergy-based Analysis of City Hotspots to Discover Trends and Anomalies in Urban Transportation Usage by Alfeo, Antonio L.; Cimino, Mario G. C. A.; Egidi, Sara; Lepri, Bruno; Vaglini, Gigliola is a scholarly article available to read on EtoBox.

What is A Stigmergy-based Analysis of City Hotspots to Discover Trends and Anomalies in Urban Transportation Usage about?

A key aspect of a sustainable urban transportation system is the effectiveness of transportation policies. To be effective, a policy has to consider a broad range of elements, such as pollution emission, traffic flow, and human mobility. Due to the complexity and variability of these elements in the urban area, to produce effective policies remains a very challenging task. With the introduction of the smart city paradigm, a widely available amount of data can be generated in the urban spaces. Such data can be a fundamental source of knowledge to improve policies because they can reflect the sustainability issues underlying the city. In this context, we propose an approach to exploit urban positioning data based on stigmergy, a bio-inspired mechanism providing scalar and temporal aggregation of samples. By employing stigmergy, samples in proximity with each other are aggregated into a functional structure called trail. The trail summarizes relevant dynamics in data and allows matching them, providing a measure of their similarity. Moreover, this mechanism can be specialized to unfold specific dynamics. Specifically, we identify high-density urban areas (i.e hotspots), analyze their

Author

Alfeo, Antonio L.; Cimino, Mario G. C. A.; Egidi, Sara; Lepri, Bruno; Vaglini, Gigliola

Published

2018

Language

EN