VIVO: A secure, privacy-preserving, and real-time crowd-sensing framework for the Internet of Things
Artikel i vetenskaplig tidskrift, 2018

Smartphones are a key enabling technology in the Internet of Things (IoT) for gathering crowd-sensed data. However, collecting crowd-sensed data for research is not simple. Issues related to device heterogeneity, security, and privacy have prevented the rise of crowd-sensing platforms for scientific data collection. For this reason, we implemented VIVO, an open framework for gathering crowd-sensed Big Data for IoT services, where security and privacy are managed within the framework. VIVO introduces the enrolled crowd-sensing model, which allows the deployment of multiple simultaneous experiments on the mobile phones of volunteers. The collected data can be accessed both at the end of the experiment, as in traditional testbeds, as well as in real-time, as required by many Big Data applications. We present here the VIVO architecture, highlighting its advantages over existing solutions, and four relevant real-world applications running on top of VIVO. (C) 2018 Elsevier B.V. All rights reserved.

Mobile crowd-sensing

Internet of Things

Big data


Luca Luceri

Universität Bern


Felipe Cardoso


Michela Papandrea


Silvia Giordano


Julia Buwaya

Universite de Geneve

Stephane Kundig

Universite de Geneve

Constantinos Marios Angelopoulos

Bournemouth University

Universite de Geneve

Jose Rolim

Universite de Geneve

Zhongliang Zhao

Universität Bern

Jose Luis Carrera

Universität Bern

Torsten Braun

Universität Bern

Aristide Tossou

Chalmers, Data- och informationsteknik, Datavetenskap

Christos Dimitrakakis

Chalmers, Data- och informationsteknik, Data Science

Aikaterini Mitrokotsa

Chalmers, Data- och informationsteknik, Nätverk och system

Pervasive and Mobile Computing

1574-1192 (ISSN)

Vol. 49 126-138


Informations- och kommunikationsteknik


Datavetenskap (datalogi)




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