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Conceptualization of Methods and Experiments in Data Intensive Research Domains Read chapter Read first chapter

2017 | OriginalPaper | Chapter

On Data Persistence Models for Mobile Crowdsensing Applications

Authors : Dmitry Namiot, Manfred Sneps-Sneppe

Published in: Data Analytics and Management in Data Intensive Domains

Publisher: Springer International Publishing

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Abstract

In this paper, we discuss various models and solutions for saving data in crowdsensing applications. A mobile crowdsensing is a relatively new sensing paradigm based on the power of the crowd with the sensing capabilities of mobile devices, such as smartphones, wearable devices, cars with mobile equipment, etc. This conception (paradigm) becomes quite popular due to huge penetration of mobile devices equipped with multiple sensors. The conception enables to collect local information from individuals (they could be human persons or things) surrounding environment with the help of sensing features of the mobile devices. In our paper, we provide a review of the data persistence solutions (back-end systems, data stores, etc.) for mobile crowdsensing applications. The main goal of our research is to propose a software architecture for mobile crowdsensing in Smart City services. The deployment for such kind of applications in Russia has got some limitations due to legal restrictions also discussed in our paper.

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Metadata
Title
On Data Persistence Models for Mobile Crowdsensing Applications
Authors
Dmitry Namiot
Manfred Sneps-Sneppe
Copyright Year
2017
Book
Data Analytics and Management in Data Intensive Domains

Print ISBN: 978-3-319-57134-8

Electronic ISBN: 978-3-319-57135-5

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-57135-5_14

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