Wildfire Data Network for Predictive Response Coordination
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Solution Overview
Problem
Existing systems fail to provide integrated, predictive, and adaptive strategies for wildfire management and suppression due to overwhelming raw data volume and lack of determinative information, leading to ineffective emergency response and fire management.
Innovation Solution
A networked system comprising mobile and fixed units with processors and GUIs that process raw data to derive predictive information, enabling adaptive strategies and virtual simulations for wildfire management and suppression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If large amounts of raw data are collected and presented in visually stimulating ways, then data availability and presentation quality are improved, but data usability and clarity deteriorate due to confusion and lack of determinative information
Solution Approach 1:
The system extracts only the most relevant and determinative features from the overwhelming raw data stream. Machine learning models identify and extract key patterns related to fire behavior, resource needs, and risk assessment, presenting only this extracted information to decision-makers rather than the complete raw dataset.
Solution Approach 2:
The patent introduces an intermediary layer of artificial intelligence and machine learning algorithms between the raw data sources and the end users. This intermediary processes, analyzes, and translates raw data into actionable insights, bridging the gap between data availability and data usability.
2Adaptability or versatility
If multiple agencies and groups respond to wildfires with different strategies, then response coverage is improved, but integrated strategy implementation deteriorates due to coordination complexity
Solution Approach 1:
The system merges data, communication channels, and decision-making processes from multiple agencies into a single integrated platform. All participating agencies contribute their capabilities while the central AI system coordinates their actions, combining diverse response capabilities into a unified strategy.
Solution Approach 2:
The patent creates a universal communication and coordination platform that serves multiple agencies with different functions and requirements. The system adapts to various agency needs while maintaining a common framework for integrated decision-making and resource allocation.
3Reliability
If real-time data from multiple sources is collected, then situational awareness is improved, but processing time and computational requirements worsen
Solution Approach 1:
The system performs preliminary processing and analysis of data streams as they arrive, using machine learning models to pre-identify patterns and predict future states. This preliminary action reduces the computational burden during critical decision-making moments and enables faster response times.
Solution Approach 2:
The patent implements continuous real-time processing of data streams without interruption, maintaining constant situational awareness. The system processes data continuously as it arrives, updating predictions and alerts in real-time rather than batch-processing, ensuring uninterrupted monitoring and response capability.
Data Source
AI summary
There is provided networks, systems and displays for providing derived data and predictive information for use in emergencies; and in particular for use in wildfire emergencies. More particularly, there is provided systems, equipment and networks for the monitoring and collecting of raw data regarding fire emergencies, both real time and historic. In embodiments, this raw data is then analyzed to provide derived data, predictive data, virtual data, and combinations and variations of this data, which depending upon the nature of this data may be packaged, distributed, displayed and used in various setting and applications to mitigate, avoid and manage the emergency, including a wildfire emergency.