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Quantify Resilience Enhancement of UTS through Exploiting Connected Community and Internet of Everything Emerging Technologies

Published:26 October 2017Publication History
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Abstract

This work aims at investigating and quantifying the Urban Transport System (UTS) resilience enhancement enabled by the adoption of emerging technology such as Internet of Everything (IoE) and the new trend of the Connected Community (CC). A conceptual extension of Functional Resonance Analysis Method (FRAM) and its formalization have been proposed and used to model UTS complexity. The scope is to identify the system functions and their interdependencies with a particular focus on those that have a relation and impact on people and communities. Network analysis techniques have been applied to the FRAM model to identify and estimate the most critical community-related functions. The notion of Variability Rate (VR) has been defined as the amount of output variability generated by an upstream function that can be tolerated/absorbed by a downstream function, without significantly increasing of its subsequent output variability. A fuzzy-based quantification of the VR based on expert judgment has been developed when quantitative data are not available. Our approach has been applied to a critical scenario as flash flooding considering two cases: when UTS has CC and IoE implemented or not. However, the method can be applied in different scenarios and critical infrastructures. The results show a remarkable VR enhancement if CC and IoE are deployed.

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        • Published in

          cover image ACM Transactions on Internet Technology
          ACM Transactions on Internet Technology  Volume 18, Issue 1
          Special Issue on Connected Communities
          February 2018
          250 pages
          ISSN:1533-5399
          EISSN:1557-6051
          DOI:10.1145/3155100
          • Editor:
          • Munindar P. Singh
          Issue’s Table of Contents

          Copyright © 2017 ACM

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 26 October 2017
          • Accepted: 1 August 2017
          • Revised: 1 July 2017
          • Received: 1 July 2016
          Published in toit Volume 18, Issue 1

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