Participant selection in CrowdSensing environments

CrowdSensing is rooted in Participatory Sensing and crowdsourcing and is defined as a paradigm that harnesses the power of the masses and embedded sensors in smart mobile devices to collect data to be used around a specific target [1]. CrowdSensing has been researched and developed by various authors in different contexts, demonstrating its usefulness to support various processes by offering the ability to generate and maximize the usefulness of the information adding contextual information. This paper presents in an integrated manner the concepts around CrowdSensing and identifies the selection of participants as the main challenge of this paradigm. Finally, a strategy is proposed to address this challenge and how was applied to two case studies.