Abstract
Propagating crowdsourcing services via a wireless network can be an appropriate solution to using the potential of crowds in crisis management processes. The present study aimed to deploy crowdsourcing services properly to spatial urgent requests. Composing such atomic services can conquer sophisticated crisis management. In addition, the conducted propagated services guide people through crisis fields and allow managers to use crowd potential appropriately. The use of such services requires a suitable automated allocation method, along with a proper approach to arranging the sequence of propagating services. The solution uses a mathematical framework in the context of a GIS (Geospatial Information System) in order to construct an allocation approach. Solution elements are set out in a multi-agent environment structure, which simulate disaster field objects. Agents which are dynamically linked to objects in a crisis field, interact with each other in a competitive environment, and the results in forming crowdsourcing services are used to guide crowds in the crisis field via the crowdsourcing services. The present solution was implemented through a proper data schema in a powerful geodatabase, along with various users with specialized interfaces. Finally, a solution and crowdsourcing service was tested in the context of a GIS in the 2019 Aqala flood disaster in Iran and other complement scenarios. The allocating performance and operation of other system elements were acceptable and reduced indicators, such as rescuer fatigue and delay time. Crowdsourcing service was positioned well in the solution and provided good performance among the elements of the Geospatial Information System.
Highlights
The elimination of natural hazard consequences is usually difficult due to their huge extent [1] in spatial and temporal scale, field recognition [2], and effective management [3]
The map is based on the information obtained from the such maps by the GI system is very effective for crisis management, and secondly, Team 1 has crowdsourcing service
We believe that the use of spatial crowdsourcing services can create new developments in spatial information systems
Summary
The elimination of natural hazard consequences is usually difficult due to their huge extent [1] in spatial and temporal scale, field recognition [2], and effective management [3]. Using some methods, such as data fusion [4] can solve some problems to some extent, issues, such as monitoring, resource management, services, financing [5], ensuring effectiveness of actions taken, reducing reacting time and delivering services, resilience [6], and creating widespread coverage with minimal resources are among the challenges that require a more robust solution. In this regard, crowdsourcing potentials can be regarded as a proper solution to cover the above-mentioned deficiencies [7].
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