Pedestrian pathways are a crucial networking components of our cities, and yet they are somehow seen as subordinate to streets in many areas that are not central. As a result, detection of their actual status, and corresponding maintenance, is often far from optimal. In this work we look for solutions to the problem of pathways status detection, and look for novel solutions that allow us to assess the status of a pedestrian pathway. We develop a system that enables to collect data from the pathways in a very economical and flexible way, and then experiment to see whether the data allow to actually produce a reliable status prediction. The results, tested on the field, show that the obtained system is both convenient to use and precise, paving the way for better ways of handling pedestrian pathways networking within a smarter city environment.

Fix Me Up: Smart Pathways Status Detection

Marchiori, Massimo
2018

Abstract

Pedestrian pathways are a crucial networking components of our cities, and yet they are somehow seen as subordinate to streets in many areas that are not central. As a result, detection of their actual status, and corresponding maintenance, is often far from optimal. In this work we look for solutions to the problem of pathways status detection, and look for novel solutions that allow us to assess the status of a pedestrian pathway. We develop a system that enables to collect data from the pathways in a very economical and flexible way, and then experiment to see whether the data allow to actually produce a reliable status prediction. The results, tested on the field, show that the obtained system is both convenient to use and precise, paving the way for better ways of handling pedestrian pathways networking within a smarter city environment.
2018
2018 International Symposium on Networks, Computers and Communications, ISNCC 2018
2018 International Symposium on Networks, Computers and Communications, ISNCC 2018
9781538637784
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3299872
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