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Thresholds for test fires?
For the prize (click "show" below to see Proposed Prize Design), we are envisioning that fires should not be suppressed by teams until they reach a certain threshold—this is to ensure that the autonomous systems being developed don’t inadvertently drop water on people BBQing or having campfires.
Proposed Prize:
What would an appropriate threshold be? We’ve had it suggested we should be looking at infrared heat signatures—would that be a good way to think of a threshold? Or would fire behavior (flame length, rate of spread), be better measures for a threshold worth attacking? If so, what is the right cut-off number and why?
Is there another way altogether to ensure that people making small campfires are not targeted by the systems developed in this competition?
Share any thoughts, examples, ideas, or comments you may have!
Proposed Prize:
We are interested in focusing a prize specifically on wildfire suppression. In light of the increasing risk to lives and assets, the focus is on suppression of Wildland-Urban Interface fires, before these escalate into large fire events that put communities at risk. Here is an initial description of a proposed prize. In the other topics in the community, you’ll find different categories of feedback we would love to get on this design.
We understand that a prize designed in this way may result in a different approach or paradigm for firefighting, and we invite you to explore—for example, with faster detection and response, can fires be extinguished without traditional containment and control strategies?
The Proposed Prize: We are proposing a prize that works something like the following: Teams are invited to test a fully integrated autonomous system that rapidly detects, responds and suppresses wildfires. There will be a competition testing area of X by X acres (NOTE: we are proposing testing in an outdoor environment). At the beginning of the test, competition officials will ignite a fire somewhere within the testing grid. Once Y threshold of spread, temperature, flame height, or another variable is crossed, the competing team will have Z minutes to detect and completely extinguish the fire. The overall cost of the teams’ system must be no more than C dollars. Solutions must not pose an risk to the environment and/or lives.
We understand that a prize designed in this way may result in a different approach or paradigm for firefighting, and we invite you to explore—for example, with faster detection and response, can fires be extinguished without traditional containment and control strategies?
The Proposed Prize: We are proposing a prize that works something like the following: Teams are invited to test a fully integrated autonomous system that rapidly detects, responds and suppresses wildfires. There will be a competition testing area of X by X acres (NOTE: we are proposing testing in an outdoor environment). At the beginning of the test, competition officials will ignite a fire somewhere within the testing grid. Once Y threshold of spread, temperature, flame height, or another variable is crossed, the competing team will have Z minutes to detect and completely extinguish the fire. The overall cost of the teams’ system must be no more than C dollars. Solutions must not pose an risk to the environment and/or lives.
What would an appropriate threshold be? We’ve had it suggested we should be looking at infrared heat signatures—would that be a good way to think of a threshold? Or would fire behavior (flame length, rate of spread), be better measures for a threshold worth attacking? If so, what is the right cut-off number and why?
Is there another way altogether to ensure that people making small campfires are not targeted by the systems developed in this competition?
Share any thoughts, examples, ideas, or comments you may have!
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Comments
Also we mentioned BBQing and campfires above, but another category of "good" fire we might want to threshold out would be prescribed burns or agricultural fires. How can we make sure our autonomous system is sensitive (and fast) enough to put out potential megafires before they spread without attacking these fires that don't warrant a response?
A more factual measure is the fire intensity, or the heat-release rate per unit length of Fireline, however this is very difficult to measure. A high fire intensity in one space doesn't indicate things are all lost if it's over a small area as well, so there is a complication to how these limits are defined.
I feel like something missing from this conversation is input from more people who actually work as fire managers. They may have some specific situations that are problematic where a more specific solution could be looked at.
Re: acreage ...another way of thinking about this threshold questions, is we're trying to figure out 2 thresholds, the first being "what signifies that a fire is significant enough to target" (and not a camp fire say) and the second being "what is the maximum threshold we can tolerate" before the fire gets out of control? "
I'm assuming the 5-10 acres you refer is basically the second threshold (what is the biggest possible fire we can tolerate before it's out of control). Any thoughts on what the first type of threshold might be (i.e. what is the size at which a supression system should bother targeting and trying to suppress in the first place?) We've heard some experts talk about fire perimeter of maybe a couple meters square as being a good initial threshold?
Re: more people who work as fire managers, completely agree and actively working to find these people and get them into the community! If you (or anyone else reading this) know of any working fire managers or incident commanders, please let us know (feel free to reach out to me at my xprize email if you prefer), and we'd love to invite them in!
Maybe it would be helpful as a starting point to think through all the false positives we would want to rule out, specifically in the WUI. So far a list might look something like:
* "Recreational" fires (campfires, BBQs etc.)
* Agricultural fires
* Reflections
* Oil or gas fires
Anything else I'm missing that might make such a list of false positives to avoid? Are there any common thresholds or metrics we could use as a way of making sure teams' solutions aren't responding
Also, to your point about "time from initiation"...I'm assuming you mean the time teams have to suppress the fire once it's ignited? We just started a discussion topic here to discuss that exact thing.
Above I talked about some of the examples of false positives that should NOT be attacked by the teams' solutions--specifically campfires and barbecues. I think you're totally right that things like agricultural or prescribed burns as well as reflections also fall into this category.
What's challenging here is that in our prize design, we had been hoping to address false positives like campfires or barbecues with a size threshold (i.e. teams should only respond to fires once they get to a certain size), but the examples you point out, indicate that maybe having a threshold size will not solve this problem of false positives.
Maybe a helpful step would be listing all the different sorts of false positives we might want to exclude and then seeing if there are any shared characteristics amount them (physical or fire behavior) we could use as a threshold for teams to not attack. So far I think we've identified the following false positives, but please let us know if there are more:
-Agricultural burns
-Other prescribed fires (e.g. for forest thinning to prevent wildfires)
-Oil and gas fires
- Recreational fires (e.g. campfires or bbqs)
- -Reflections
Anything else?
A decision-making algorithm might include a formula like:
Fa (fire area) + Fi (fire intensity) + Frg (fire rate of growth) + Wd, h, w (weather; a composite variable of several key conditions; here; dryness, humidity, wind) = Sy/n/c (suppression effort: yes/no/continue monitoring).
Note: lower case letters are subscripts for the various (capitalized) fire and weather parameters.
1] I must add another variable to the hypothetical formula: 'fuel type' (type of timber, dead/living wood, biomass on ground, mixed fuel [i.e., shrubs, trees {previously burned?}, fallen trees, dead wood, etc.])..which will have a direct impact/influence on a fire's 'rate of growth'.
2] Am still reading over my fire forensics files/papers (will follow up again).
@mgollner - I understand that fire prediction can be as much 'art' as 'science'... Interestingly, so too is much of Forensic Science (the topic of much critical discussion/debate in recent years among the nation's scientific community)... Human interpretation (often based upon experience rather than data) plays an out-sized role in forensic determinations (e.g., whether one pattern from source A matches the pattern on source B, etc.)..this fact of subjectivity in Forensics (as applied to the law) has been criticized by the National Academy of Sciences (2009), PCAST (2016) and NIST (2017).
As it turns out, 'fire forensics' is predominantly focused on determining cause (which makes sense) and not predicting its spread (i.e., its pattern of spread, post fire extinguishing)...In point of fact, most house or building fires, once extinguished, readily reveal their spreading patterns through straightforward analysis (often an aerial photo clearly reveals where the fire originated).
So, while I am not giving up on this research path entirely, I feel it (fire forensics) has only limited applicability for our challenge design.
One other note: regarding existing fire prediction algorithms...how accurate are these predictive algorithms; have they been evaluated against real world data? I am assuming so, but i would like to see the research myself.
There are many "small" false positives from satellites. Single pixels won't necessarily dispatch a fire department, rarely do people watch the satellite feed until they have a problem. This thought process is changing but I don't know what will be implemented. There's a variety of false positives that are real events that just don't really mean they're a wildfire. Many papers by Giglio et al. and Schroder et al. from Univ. Maryland and NOAA on this.
There is a good comment in the technical documentation for FARSITE talking about "model validation". I'd agree with his assessment it's not entirely possible for large scale fires quite yet. There's work by Rod Linn using a full 3D solver, FIRETEC recreating fires run at Eglin AFB as well, these were so incredibly sensitive to the wind sensors that you see it's very hard to do any true validation scheme at this time. But these algorithms are relatively good when "gaming", I.e. looking at one action vs. another and seeing how the outcome will change, even if the absolute value may be off. in other words, the trends are generally correct. Using real-time data, like data assimilation, is an approach we've suggested would be very beneficial for the field, that's in large part to how weather predictions have improved so much.