Abstract

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 …

Date

November 5, 2025

Authors

Luca Luceri, Felipe Cardoso, Michela Papandrea, Silvia Giordano, Julia Buwaya, Stephane Kundig, Constantinos Marios Angelopoulos, Jose Rolim, Zhongliang Zhao, Jose Luis Carrera, Torsten Braun, Aristide Charles Yedia Tossou, Christos Dimitrakakis

Journal

Pervasive and Mobile Computing

Publisher

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