Flood Management in Aqala through an Agent-Based Solution and Crowdsourcing Services in an Enterprise Geospatial Information System

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.

Agent-based modelling and flood risk management: A compendious literature review

“…Another interesting study was conducted by Li et al (2019), which combined a cellular automata model and a ABM system to simulate crowd evacuations in flood disasters, and the model was evaluated by real-participant experiments based on virtual reality (VR) environments. Similar studies on ABM applications in flood evacuation are also found in Higo et al (2017); Lim (2016, 2018); Yamamoto and Takizawa (2019); Nakanishi et al (2019); and Eivazy and Malek (2019).…”

Advanced Technologies for Offering Situational Intelligence in Flood Warning and Response Systems: A Literature Review

“…[70] Evacuation (estimated and actual) Evacuation planning and relief management [35,63] Affected population Plan rescue operation and provide emergency treatments. [37,62,63,70,82,83] Intelligence related to infrastructure at risk…”

A Blockchain-Based Spatial Crowdsourcing System for Spatial Information Collection Using a Reward Distribution

“…Different categories are provided for spatial crowdsourcing applications [ 30 ]. Applying spatial crowdsourcing to gathering information in a specific location [ 40 , 41 , 42 , 43 , 44 , 45 , 46 ], answering spatial queries, and using local people’s knowledge to solve problems within a particular area are applications of this concept [ 47 , 48 , 49 , 50 ]. In addition, spatial crowdsourcing is used in location-based services to detect traffic incident [ 51 ].…”