# US 11,998,783 B1 · Wildfire cone of confidence simulation system and processes

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- Number: US 11,998,783 B1
- Document ID: US11998783B1
- Status: Granted
- Kind: B1
- Application number: 18/376,104
- Filed: 2023-10-03
- Granted: 2024-06-04
- Earliest claimed: 2022-10-04
- Applicants: Rachael Irene Brady
- Inventors: Rachael Irene Brady
- Web page: https://patentgrep.com/patent/US11998783B1

## CPC

- A62C 99/009: {Methods or equipment not provided for in groups A62C99/0009 - A62C99/0081}
- A62C 3/0271: {Detection of area conflagration fires (fire alarms for forest fires G08B17/005)}
- A62C 3/02: for area conflagrations, e.g. forest fires, subterranean fires
- A62C: FIRE-FIGHTING (fire-extinguishing compositions, use of chemical substances in extinguishing fires A62D1/00; spraying, applying liquids or other fluent materials to surfaces in general B05; alarm arrangements G08B, e.g. fire alarms actuated by smoke or gases G08B17/10)

## Abstract

A wildfire cone of confidence simulation system and processes is disclosed. Methodical application of the hurricane cone of confidence applied to wildfire simulations involves applying a methodology that has been utilized in the hurricane disaster space since the 1950s, to the current wildfire predictive modeling problem. As wildfires become larger and move more quickly the public requires notifications that are consumable and actionable.

## Claims

### Claim 1

A wildfire cone of confidence simulation process comprising:
running a particular wildfire simulation (“WS”) for a fire on one wildfire propagation model of multiple wildfire simulation models, wherein the wildfire propagation model is configured to output a WS result (“WS result output”) after running the particular WS;
compiling the particular WS into a path and a direction the fire is likely to take based on the WS result output;
overlaying fire history information onto the WS result output;
compiling a weighted overlay of the particular WS and the fire history;
applying a statistical probability of fire path, direction, and timing based on outputs of the weighted overlay;
creating a wildfire cone of confidence;
identifying areas in which the weighted overlay of the particular WS and the fire history aligns within two standard deviations of a mean;
adding the identified areas in the wildfire cone of confidence;
displaying the wildfire cone of confidence on a mapping interface with a plurality of highlighted time frame intervals; and
applying an evacuation buffer to the wildfire cone of confidence to aid emergency responders.

### Claim 2 (depends on 1)

The wildfire cone of confidence simulation process of claim 1, wherein the plurality of highlighted time frame intervals comprises a one hour time frame interval.

### Claim 3 (depends on 1)

The wildfire cone of confidence simulation process of claim 1, wherein the plurality of highlighted time frame intervals comprises a two hour time frame interval.

### Claim 4 (depends on 1)

The wildfire cone of confidence simulation process of claim 1, wherein the plurality of highlighted time frame intervals comprises a three hour time frame interval.

### Claim 5 (depends on 1)

The wildfire cone of confidence simulation process of claim 1 further comprising adding actual fire progression data to the weighted overlay of the particular WS.

### Claim 6 (depends on 5)

The wildfire cone of confidence simulation process of claim 5, wherein adding actual fire progression data comprises continually adding actual fire progression data to the weighted overlay in realtime.

### Claim 7 (depends on 5)

The wildfire cone of confidence simulation process of claim 5 further comprising recompiling the weighted overlay of the particular WS and the fire history after the actual fire progression data is added to the weighted overlay.

### Claim 8 (depends on 1)

The wildfire cone of confidence simulation process of claim 1 further comprising rerunning the particular WS with actual fire progression data as an additional input.