A Survey on Smartphone-Based Crowdsensing Solutions

© 2016 Willian Zamora et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.[EN] In recent years, the widespread adoption of mobile phones, combined with the ever-increasing number of sensors that smartphones are equipped with, greatly simplified the generalized adoption of crowdsensing solutions by reducing hardware requirements and costs to a minimum. These factors have led to an outstanding growth of crowdsensing proposals from both academia and industry. In this paper, we provide a survey of smartphone-based crowdsensing solutions that have emerged in the past few years, focusing on 64 works published in top-ranked journals and conferences. To properly analyze these previous works, we first define a reference framework based on how we classify the different proposals under study. The results of our survey evidence that there is still much heterogeneity in terms of technologies adopted and deployment approaches, although modular designs at both client and server elements seem to be dominant. Also, the preferred client platform is Android, while server platforms are typically web-based, and client-server communications mostly rely on XML or JSON over HTTP. The main detected pitfall concerns the performance evaluation of the different proposals, which typically fail to make a scalability analysis despite being critical issue when targeting very large communities of users.This work was partially supported by the Ministerio de Economia y Competitividad, Programa Estatal de Investigacion, Desarrollo e Innovacion Orientada a los Retos de la Sociedad, Proyectos I+D+I 2014, Spain, under Grant TEC2014-52690-R, the "Universidad Laica Eloy Alfaro de Manabi-ULEAM," and the "Programa de Becas SENESCYT de la Republica del Ecuador."Zamora-Mero, WJ.; Tavares De Araujo Cesariny Calafate, CM.; Cano Escribá, JC.; Manzoni, P. (2016). A Survey on Smartphone-Based Crowdsensing Solutions. Mobile Information Systems. 2016:1-26. https://doi.org/10.1155/2016/9681842126201