Dynamic Risk Map Generation for Disaster Response
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Solution Overview
Problem
Current GIS systems are unable to perform real-time multi-criteria decision analysis, relying on static data models that are inadequate for dynamic disaster response scenarios, as they do not effectively integrate and update heterogeneous data layers reflecting different scenarios and parameters over time.
Innovation Solution
A system and method utilizing Scenario Objects and Risk Objects within a GIS-MCDA framework, which performs real-time updates of attributes and variables associated with geospatial entities, generating scenario-based risk maps for prioritizing resource allocation through virtual processing components and multi-criteria decision analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static data models are used in GIS systems, then the system structure is simple and easy to implement, but the system cannot perform real-time multi-criteria decision analysis and cannot adapt to dynamic disaster response scenarios
Solution Approach 1:
The patent transforms static GIS data models into dynamic models by introducing time-dependent variables and continuous update mechanisms. The system now processes evolving disaster scenarios through real-time data integration, allowing the model state to change dynamically while maintaining computational tractability through structured update protocols.
Solution Approach 2:
The patent segments the complex decision analysis process into multiple hierarchical layers, including data acquisition layer, processing layer, and decision support layer. This segmentation allows real-time multi-criteria analysis to be performed through modular components, reducing overall system complexity while enabling advanced functionality.
2Loss of information
If heterogeneous data from multiple sources is integrated, then the comprehensiveness of disaster assessment improves, but the difficulty of data processing and synchronization increases
Solution Approach 1:
The patent introduces standardized data interfaces and normalization layers as intermediaries between heterogeneous data sources and the core analysis engine. These intermediaries translate diverse data formats into a unified structure, enabling comprehensive information integration while simplifying processing through standardized protocols.
Solution Approach 2:
The patent develops a universal data processing framework that can handle multiple data types (satellite imagery, ground sensor data, social media feeds) through a single integrated architecture. This multi-functional approach reduces processing difficulty by applying consistent methods across diverse data sources.
3Reliability
If real-time updates of multiple data layers are performed, then the relevance of disaster response information improves, but the computational resources and processing time required increase
Solution Approach 1:
The patent implements periodic update cycles with varying frequencies based on data criticality and change rates. Not all data layers are updated at the same rate - critical layers update frequently while stable layers update less often, maintaining information relevance while reducing overall computational resource consumption through differentiated update schedules.
Data Source
AI summary
This invention is a system creating risk indices, where the risk index is based on a combination of indicators. The indicators for measuring risk are adaptive and dynamic to the changing availability of disaster information and state of the system. Importantly, this research addresses two needs of emergency responders. It provides a risk-based prioritization of key geo-locations to allocate support and mitigation efforts. It provides a mechanism for prioritizing data collection and analysis efforts.