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GIS-based intelligent system for infectious disease disaster response

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GIS-based intelligent system for infectious disease disaster response
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266
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CC Attribution 3.0 Germany:
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This study addresses the lack of disaster response systems for medical and biological emergencies, aiming to develop a GIS-based platform for effective response to infectious diseases. The platform integrates pathogen detection, risk assessment, epidemiological investigation, and situational awareness using artificial intelligence and big data technologies. It leverages satellite and sensor data to analyze water pollution, providing real-time insights on contamination levels and affected areas. The system comprises seven layers for data management, interoperability, application, and security, enabling users to access geographic information and statistics. The platform's effectiveness was demonstrated through pilot case studies. In Limassol, flash floods polluted a reservoir, and the platform tracked pollution levels over time using satellite imagery and sensor data. In a Korean case, African swine fever spread near a river due to high precipitation. The platform helped assess ASF cases, plan containment strategies, and monitor tap water quality in real-time. The platform's AI-driven information database enhances infectious disease response, empowering first responders with quick detection and informed decision-making. As the system evolves and data analysis deepens, its potential for reducing industrial accidents through pattern recognition and machine learning becomes apparent.
UML
WordData managementPresentation of a groupOrder (biology)Computer animation
InformationDependent and independent variablesResultantPartial derivativeMathematical analysis
Projective planeMusical ensembleComputer animation
Continuous functionMusical ensembleModule (mathematics)
Gateway (telecommunications)Module (mathematics)Water vaporResultantGateway (telecommunications)Program flowchart
Module (mathematics)Decision support systemComputing platformInformation
Texture mappingDisintegrationData managementSatelliteConditional-access moduleModule (mathematics)
Overlay-NetzInformationPoint (geometry)Electronic visual displayPoint (geometry)Electronic visual displayImplementationComputer animation
Data managementMereologyComputer animation
Computer animation
Electronic mailing listLevel (video gaming)
InformationInformationTable (information)Module (mathematics)Computer animation
Level (video gaming)Selectivity (electronic)InformationComputer animation
LogicTable (information)Computer animation
Texture mappingGeometryWater vaporTable (information)InformationGreen's functionConcentricFood energyComputer animation
InformationComputer animation
Musical ensembleSatelliteExtension (kinesiology)CASE <Informatik>Dependent and independent variablesDenial-of-service attackTable (information)Computing platformEstimatorAreaComputer animation
Linear mapInterpolationSatelliteTwitterCartesian coordinate systemMedical imagingComputer animation
Transcript: English(auto-generated)
Hello, my name is Min Young Lee from South Korea. Let's begin. The presentation is in the order of background, word description, situation monitoring, and management.
The background, there are various risks due to water pollution caused by climate change. The purpose is to prepare emergency response methods
and technique for pathogen pollution through partial information based analysis results. The PESSTOR project is a consortium of 23 partners from Europe and Korea.
The goal is that quickly detects waterborne pathogens and induce cooperation among various stakeholders in emergencies. There are modules related to images,
pathoset, CAM, and drone. These are used to continuously monitor water quality. Next are modules for checking and responding to the situation. PathTweet monitors data to filter
what it deems to be a risk. And PathSense is an IoT gateway measuring the water quality. The monitoring results in various modules mentioned above can be received through Alletra.
It is a pathoGIS that combines these modules to provide the information. Use the pathoGIS platform to detect water and manage the disaster situation for decision support.
Each data is collected, processed, and delivered through PESSTORware so that it can be monitored by PESSTORGIS. PESSTORGIS provides the following features.
Scenario-based implementation and point data display and so on. Situation monitoring and management parts. If you log in to the platform,
select a scenario from the globe map. You can see the information on the modules can be found in the content table. The information is shown in the data table below.
Each information is displayed partially on the map and details are displayed when selected. It can filter the data in the table to view it within the desired logic.
Click the information. The table to see the green energy concentration in the water. You can check the abnormal information
that occurs in PESSTORSense or PESSTORTEET through the alarm. To pilot, yes. Use cases are designed to test the use of the platform.
The first is an arts case in Limassol, Cyprus. Flooding occurs in the river and analyze the river through satellite image. Next, estimate the extent of the flood-stricken area.
Finally, respond to the situation on the table in the region. The second one is, applicants are in the river.
The river also analyze the, with satellite image. And partially, interpolation analyzes, so we get the water pollution trends. Final step, people respond to the situation by tweet.
And the end. Thank you.