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Crowdsensing can provide real time and detailed information about rapidly evolving crisis situations to facilitate rapid response and effective resource allocation. But while challenges such as heterogeneity of data content and quality, asynchronicity, and volume call for robust data integration and interpretation capabilities, situation awareness in crowdsensing for crisis management remains a largely unexplored area of research. In this paper we extend the mobile4D smartphone-based disaster reporting and alerting system with a situation awareness data interpretation and integration layer and demonstrate its application to the problem of tracking cholera outbreaks. The communication workflow in mobile4D-SA supports interaction between crowdsensed information, system predictions, and multifaceted communication between authorities and affected people on the ground.
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Haddawy et al. (2015) studied this question.