  Crowdsourcing models applied to work on mobile devices continuously reach new
ways of solving sophisticated problems, now with a use of portable advanced
devices, where users are not limited to a stationary use. There exists an open
problem of quality in crowdsourcing models due the inexperienced or malicious
workers. In this paper, we propose a model and a short specification of a
platform for a bundled widely available crowdsourcing mechanism, which tries to
utilize workers individual characteristics to maximum. Analyzed solution relies
on geographical data classified by localization category. Secondly, we profile
mobile workers by precisely analyzing their activity history. Results of this
research will make an impact on better understanding the latent potential of
mobile devices users. It makes for not only better quality in results, but also
opens a possibility of implementing a "twitch crowdsourcing" or emergency
relief systems. Special tasks assigned to owners of mobile devices can help
those, which are in need of help, making them the task creators.
