Abstract

This paper provides the vision of a unified spatial crowdsourcing platform that is designed to efficiently tackle different types of spatial tasks which have been gaining a lot of popularity in recent years. Several examples of spatial tasks are ride-sharing services, delivery services, translation tasks, and crowd-sensing tasks. While existing crowdsourcing platforms, such as Amazon Mechanical Turk and Upwork, are widely used to solve lots of general tasks, e.g., image labeling; using these marketplaces to solve spatial tasks results in low quality results. This paper identifies a set of characteristics for a unified spatial crowdsourcing environment and provides the core components of the platform that are required to empower the capability in solving different types of spatial tasks.

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