Applying Fog Computing to Improve Crime Assistance in Smart Transportation Safety Systems

Hugo B. Camboim; Augusto J.Venancio Neto; Joel J.P.C. Rodrigues; Zhongliang Zhao

doi:10.1109/S3C.2017.8501398

Applying Fog Computing to Improve Crime Assistance in Smart Transportation Safety Systems

Hugo B. Camboim
, Augusto J.Venancio Neto
, Joel J.P.C. Rodrigues
, Zhongliang Zhao

Universidade Federal do Rio Grande do Norte
Instituto de Telecomunicações
Instituto Nacional de Telecomunicações
Universidade de Fortaleza
University of Bern

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

Smart Transportation Safety (STS) envisions to improve public safety through a significant paradigm shift in today's reactive way that police authorities respond to crimes to a pro-active one. The application of smart surveillance in STS allows automatically identifying potential security threats in the target environment with agility and accuracy. Fog computing promises to enhance the cloud smart surveillance enabled STS systems, by avoiding the additional latency rates raised by the round trips to faraway data centers. In this paper, the FISVER framework is proposed to apply new ICT paradigms in smart surveillance capable STS systems to enhance crime assistance. Through FISVER, in-vehicle fog and Fog systems interwork to provision autonomous crime detections and real-time crime assist at bus service. FISVER's prototyping over a real testbed raises evaluation outcomes that demonstrate its essential contribution to mission critical situations, highlighting outstanding system performance and mobile device survivability rates in comparison to a typical STS use case.

Original language	English
Title of host publication	2017 IEEE 1st Summer School on Smart Cities, S3C 2017 - Proceedings
Editors	Everton Cavalcante, Gilles Betis, Thais Batista, Rosaldo Rossetti, Nelio Cacho
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	19-24
Number of pages	6
ISBN (Electronic)	9781538610633
DOIs	https://doi.org/10.1109/S3C.2017.8501398
State	Published - 19 Oct 2018
Externally published	Yes
Event	1st IEEE Summer School on Smart Cities, S3C 2017 - Natal, Brazil Duration: 6 Aug 2017 → 11 Aug 2017

Publication series

Name	2017 IEEE 1st Summer School on Smart Cities, S3C 2017 - Proceedings

Conference

Conference	1st IEEE Summer School on Smart Cities, S3C 2017
Country/Territory	Brazil
City	Natal
Period	6/08/17 → 11/08/17

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities
SDG 16 Peace, Justice and Strong Institutions

Keywords

Autonomous System
Fog Computing
Intelligent Computing
Smart Surveillance
Smart Transportation Safety

Access to Document

10.1109/S3C.2017.8501398

Cite this

Camboim, H. B., Neto, A. J. V., Rodrigues, J. J. P. C., & Zhao, Z. (2018). Applying Fog Computing to Improve Crime Assistance in Smart Transportation Safety Systems. In E. Cavalcante, G. Betis, T. Batista, R. Rossetti, & N. Cacho (Eds.), 2017 IEEE 1st Summer School on Smart Cities, S3C 2017 - Proceedings (pp. 19-24). Article 8501398 (2017 IEEE 1st Summer School on Smart Cities, S3C 2017 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/S3C.2017.8501398

Camboim, Hugo B. ; Neto, Augusto J.Venancio ; Rodrigues, Joel J.P.C. et al. / Applying Fog Computing to Improve Crime Assistance in Smart Transportation Safety Systems. 2017 IEEE 1st Summer School on Smart Cities, S3C 2017 - Proceedings. editor / Everton Cavalcante ; Gilles Betis ; Thais Batista ; Rosaldo Rossetti ; Nelio Cacho. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 19-24 (2017 IEEE 1st Summer School on Smart Cities, S3C 2017 - Proceedings).

@inproceedings{d23b33477b724917834ef66c7de40e12,

title = "Applying Fog Computing to Improve Crime Assistance in Smart Transportation Safety Systems",

abstract = "Smart Transportation Safety (STS) envisions to improve public safety through a significant paradigm shift in today's reactive way that police authorities respond to crimes to a pro-active one. The application of smart surveillance in STS allows automatically identifying potential security threats in the target environment with agility and accuracy. Fog computing promises to enhance the cloud smart surveillance enabled STS systems, by avoiding the additional latency rates raised by the round trips to faraway data centers. In this paper, the FISVER framework is proposed to apply new ICT paradigms in smart surveillance capable STS systems to enhance crime assistance. Through FISVER, in-vehicle fog and Fog systems interwork to provision autonomous crime detections and real-time crime assist at bus service. FISVER's prototyping over a real testbed raises evaluation outcomes that demonstrate its essential contribution to mission critical situations, highlighting outstanding system performance and mobile device survivability rates in comparison to a typical STS use case.",

keywords = "Autonomous System, Fog Computing, Intelligent Computing, Smart Surveillance, Smart Transportation Safety",

author = "Camboim, \{Hugo B.\} and Neto, \{Augusto J.Venancio\} and Rodrigues, \{Joel J.P.C.\} and Zhongliang Zhao",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 1st IEEE Summer School on Smart Cities, S3C 2017 ; Conference date: 06-08-2017 Through 11-08-2017",

year = "2018",

month = oct,

day = "19",

doi = "10.1109/S3C.2017.8501398",

language = "英语",

series = "2017 IEEE 1st Summer School on Smart Cities, S3C 2017 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "19--24",

editor = "Everton Cavalcante and Gilles Betis and Thais Batista and Rosaldo Rossetti and Nelio Cacho",

booktitle = "2017 IEEE 1st Summer School on Smart Cities, S3C 2017 - Proceedings",

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}

Camboim, HB, Neto, AJV, Rodrigues, JJPC & Zhao, Z 2018, Applying Fog Computing to Improve Crime Assistance in Smart Transportation Safety Systems. in E Cavalcante, G Betis, T Batista, R Rossetti & N Cacho (eds), 2017 IEEE 1st Summer School on Smart Cities, S3C 2017 - Proceedings., 8501398, 2017 IEEE 1st Summer School on Smart Cities, S3C 2017 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 19-24, 1st IEEE Summer School on Smart Cities, S3C 2017, Natal, Brazil, 6/08/17. https://doi.org/10.1109/S3C.2017.8501398

Applying Fog Computing to Improve Crime Assistance in Smart Transportation Safety Systems. / Camboim, Hugo B.; Neto, Augusto J.Venancio; Rodrigues, Joel J.P.C. et al.
2017 IEEE 1st Summer School on Smart Cities, S3C 2017 - Proceedings. ed. / Everton Cavalcante; Gilles Betis; Thais Batista; Rosaldo Rossetti; Nelio Cacho. Institute of Electrical and Electronics Engineers Inc., 2018. p. 19-24 8501398 (2017 IEEE 1st Summer School on Smart Cities, S3C 2017 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Applying Fog Computing to Improve Crime Assistance in Smart Transportation Safety Systems

AU - Camboim, Hugo B.

AU - Neto, Augusto J.Venancio

AU - Rodrigues, Joel J.P.C.

AU - Zhao, Zhongliang

PY - 2018/10/19

Y1 - 2018/10/19

N2 - Smart Transportation Safety (STS) envisions to improve public safety through a significant paradigm shift in today's reactive way that police authorities respond to crimes to a pro-active one. The application of smart surveillance in STS allows automatically identifying potential security threats in the target environment with agility and accuracy. Fog computing promises to enhance the cloud smart surveillance enabled STS systems, by avoiding the additional latency rates raised by the round trips to faraway data centers. In this paper, the FISVER framework is proposed to apply new ICT paradigms in smart surveillance capable STS systems to enhance crime assistance. Through FISVER, in-vehicle fog and Fog systems interwork to provision autonomous crime detections and real-time crime assist at bus service. FISVER's prototyping over a real testbed raises evaluation outcomes that demonstrate its essential contribution to mission critical situations, highlighting outstanding system performance and mobile device survivability rates in comparison to a typical STS use case.

AB - Smart Transportation Safety (STS) envisions to improve public safety through a significant paradigm shift in today's reactive way that police authorities respond to crimes to a pro-active one. The application of smart surveillance in STS allows automatically identifying potential security threats in the target environment with agility and accuracy. Fog computing promises to enhance the cloud smart surveillance enabled STS systems, by avoiding the additional latency rates raised by the round trips to faraway data centers. In this paper, the FISVER framework is proposed to apply new ICT paradigms in smart surveillance capable STS systems to enhance crime assistance. Through FISVER, in-vehicle fog and Fog systems interwork to provision autonomous crime detections and real-time crime assist at bus service. FISVER's prototyping over a real testbed raises evaluation outcomes that demonstrate its essential contribution to mission critical situations, highlighting outstanding system performance and mobile device survivability rates in comparison to a typical STS use case.

KW - Autonomous System

KW - Fog Computing

KW - Intelligent Computing

KW - Smart Surveillance

KW - Smart Transportation Safety

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DO - 10.1109/S3C.2017.8501398

M3 - 会议稿件

AN - SCOPUS:85057116399

T3 - 2017 IEEE 1st Summer School on Smart Cities, S3C 2017 - Proceedings

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EP - 24

BT - 2017 IEEE 1st Summer School on Smart Cities, S3C 2017 - Proceedings

A2 - Cavalcante, Everton

A2 - Betis, Gilles

A2 - Batista, Thais

A2 - Rossetti, Rosaldo

A2 - Cacho, Nelio

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 1st IEEE Summer School on Smart Cities, S3C 2017

Y2 - 6 August 2017 through 11 August 2017

ER -

Camboim HB, Neto AJV, Rodrigues JJPC, Zhao Z. Applying Fog Computing to Improve Crime Assistance in Smart Transportation Safety Systems. In Cavalcante E, Betis G, Batista T, Rossetti R, Cacho N, editors, 2017 IEEE 1st Summer School on Smart Cities, S3C 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2018. p. 19-24. 8501398. (2017 IEEE 1st Summer School on Smart Cities, S3C 2017 - Proceedings). doi: 10.1109/S3C.2017.8501398

Applying Fog Computing to Improve Crime Assistance in Smart Transportation Safety Systems

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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