Crowdsensing mobile content and context data: Lessons learned in the wild

Abstract

This paper discusses the design and development efforts made to collect data using an opportunistic crowdsensing mobile application. Relevant issues are underlined, and solutions proposed within the CHIST-ERA Macaco project for the specifics of collecting fine-grained content and context data are highlighted. Global statistics on the data gathered for over a year of collection show its quality: Macaco data provides a long-term and fine-grained sampling of the user behavior and network usage that is relevant to model and analyse for future content and context-aware networking developments.