Our speakers today, Scott Pecoriello is founder and CEO of WeatherOptics.
Jeremy Reese is our guest speaker. He is from Geisinger Health.
Matt Cronin, VP of solutions engineering here at Juvare. And I’m Jeff Urkevich, director of partnerships here at Juvare.
With that, I think we’ll do our first poll question.
Okay. What’s your biggest challenge when it comes to anticipating and responding to severe weather?
And I’ll give you guys about a minute to, to answer that one.
All across the board.
Excellent.
Okay. Looks like we’ve got pause. I’m gonna go ahead and close the poll.
Great. Thank you for that.
With that, I’ll turn things over to Scott Pecoriello from WeatherOptics. Scott, please take it away.
Thank you, Jeff. Hey, everyone. My name is Scott Pecoriello. I am a cofounder and CEO here at WeatherOptics.
WeatherOptics is the leading weather intelligence platform for supply chain, emergency management, and business continuity professionals, producing more than a hundred billion risk scores daily that uniquely predict weather’s impact on key business operations.
Some of the largest businesses and organizations in the world rely on WeatherOptics, including CVS Health, Walmart, Dallas Fort Worth International Airport, Steris, and more.
We’re all facing the same reality. Weather disruptions are no longer rare. They are frequent. They’re costly, and they’re directly impacting safety and infrastructure, and supply chains.
We went from averaging about seven billion individual weather events per year here in the US between nineteen eighty and twenty twenty. That number is now up to twenty three per year, which is about a three times increase.
Last year alone, we saw about two hundred billion in damage from twenty seven individual billion dollar weather events. Weather has a huge impact not only on one industry, but on multiple industries. One in five roadway accidents are due to weather. Almost all power outage events are due to weather, and about a quarter of all shipment or supply chain delays are weather related.
This group probably knows this better than anyone, but having a good forecast doesn’t necessarily mean that you’re ready. The real challenge is getting the right insight to the right people at the right time in a way that can actually be acted on. And that’s especially true when it comes to hurricanes and tropical events.
There was a global study on early warning systems and weather that found that while risk knowledge and forecasting are strong, really the greatest deficiencies are in that warning dissemination, the communication, and the response capability or the translation of weather data into real impact information.
Impact warnings allow for faster response times that are focused on the right operations and the right people.
And that’s really where WeatherOptics comes in. What makes us unique as a weather provider is that we predict the impact, not just the weather. So WeatherOptics combines predictive weather data with this critical geospatial infrastructure and historical based impact data to generate forecast that speak the language of the industry. Traditional forecast tell you what the weather is, but they don’t always tell you what it means. And that’s really the gap that WeatherOptics is designed to fill.
So how do we do it? Well, we’ve built a system that goes beyond just weather data. We essentially are combining this AI weather modeling with real world infrastructure data, machine learning, and and then we’re forecasting the impact of weather in ways that others aren’t able to. And it really starts with our AI weather modeling hyper.
What hyper does and what makes hyper so unique is that it blends predictive weather modeling together. It ingests real time data like satellite data, weather station data, radar data, and then it’s bias correcting in real time to pick up on what’s actually happening. So if a thunderstorm pops up or if a hurricane changes its track, WeatherOptics is picking up on that in real time and adjusting modeling for a better performance, a better outcome. It’s also trained off of history to recognize these kind of quick pattern changes, in the weather.
By doing so, we’ve been able to reduce forecast error on just the weather piece by up to forty percent when compared to other standard NOAA weather models. Now the most important piece in this whole equation of how we create our forecasts is layering in the real world contextual data. This really gives us the ability to understand how weather is going to in interact with the real world. So we’re using things like forty million connected vehicles, local infrastructure data, how susceptible a given location is to certain weather conditions, distance from river, topography, tree height and density, all of these non-weather variables that help us again understand how weather is going to interact with the real world. We then use AI and machine learning on top of that to predict what are the consequences what will be the consequences on actual business operations at a highly granular level.
And that allows us to get to these unique hyper local risk insights like you see there on the right, and produce a number of different types of products, which we’ll share on the next slides here.
So the first is our location based risk scoring. When a storm is approaching, these are the questions that you really need answers to. Right? How is it going to affect power, roads, flooding, operations, supply chain?
Our predictive indices are built to deliver exactly that, both predictive and in real time. Every score that you see here works on a zero to ten severity scale, and it predicts how critical operations are gonna be affected at a specific location. So we have our wildfire index for wildfire spreading conditions. We have road conditions index for the level of road danger, power outage index for the likelihood and also the number of customers expected to lose power.
We have an overall business disruption index, which is unique because it takes all of the other risk scores that you see here, dynamically weights them, and gives this overall risk score zero to ten, how impactful weather’s gonna be on overall business operations.
We have our flood index, which is for the risk and severity of flooding. And then we have our life and property index as well, which is still the risk to livelihood and also, the risk to property damage as well.
All of this data is global. It works on a three kilometer scale or grid, updates every fifteen minutes, forecasts go out to seven days in advance. And the important part here is that it’s available in almost every type of deliverable. So integrates directly with the facility status board, WebEOC, ArcGIS, has alerts, web based platform, API driven as well. So there’s a number of different ways that you can get this data directly.
The second kind of product that we offer is our route or road based insights. So in addition to working on a location by location basis, we also work on a route or road or shipment level basis, providing critical delay information, important information to protect drivers, and really maintaining visibility across the supply chain. So our right route API is built to, again, really monitor if there’s going to be delays and how dangerous conditions are gonna be for drivers. You can use this, for your suppliers or emergency managers, getting a sense of is supply gonna be delayed coming into a certain location or going out to a certain location.
If you have emergency drivers that are following, let’s say, evacuation plans during hurricanes before or after events. RightRoute is really built as that weather, intelligence tool that is route, or road based. And so we have a number of different components of RightRoute. I already mentioned the shipment delay time.
We call that our weather adjusted ETA, our driver risk score for level of driver danger. If a vehicle is expected to tip over due to high winds, we have very sophisticated temperature monitoring. We can predict if a road is going to close or if there’s gonna be a high likelihood of accidents, and then we also give route alternatives. So in addition to the fastest way to get from point a to point b, are there other options that shipments or drivers can take that would avoid this risk altogether?
And then lastly on here, we produce critical event based forecasting. So this allows you to monitor both large scale critical events like your hurricanes, like your floods, severe storms, and also very hyper local details of impact to give you a full picture one stop shop of all things weather management related.
It provides that kind of real time situational awareness that is crucial during some of these major weather events. So not only is WeatherOptics auto detecting these large areas of where hurricanes are expected or where flooding or severe storms are affected. But then as those things are happening in real time, so as a hurricane is coming onshore, we’re then monitoring those real time impacts and showing you to them, in our UI or in our integration with Juvare. So that includes things like five one one road incidents. We’ve scraped all the five one one state websites to show you closures, accidents, road conditions.
We feed in real time power outages. So as power goes out in a given county, we will feed that in real time.
Storm damage reports, if there’s wind damage, hail damage, tornado damage, all of that is filtered into our platform. And we’ve also now recently introduced live camera feeds to product that will be coming out in the next month here where you can see all across the country how conditions are unfolding in real time across a very large network of cameras.
We have really great data to back up the accuracy and the usefulness of our software. This is starting at the beginning of the equation here with our hyper local weather modeling called Hyper.
These are comparing Hyper forecasts to NOAA forecasts for precipitation and for wind gusts. You can see for both categories, we’re looking here in the short term, but we’re seeing up to a forty percent decrease in that weather forecast error.
That is largely due to the way that we’re training the data and also picking up on real time changes in the data. So, again, when a severe thunderstorm pops up and there’s a change in direction of a hurricane, the weather optics modeling is real time ingesting that kind of information and data and bias correcting these forecasts to improve the accuracy.
When we look at actual individual specific events, you can also see the accuracy of the impact data that we produce.
Obviously, earlier this month, there were devastating floods in Texas that left more than a hundred dead, caught many by surprise.
Our forecast and particularly our flood index was able to give notice and alerts about twenty hours before the severe flooding began.
Again, that was looking at contextual data from our flood index. So not only looking at rainfall, but looking at topography, distance from river, slope of roadway, population density, flood zones, all of these different non weather critical pieces of information that allowed us to predict high impact flooding forecasts six hours before flood watches were issued by the National Weather Service, sixteen hours before flash flood warnings were issued by the National Weather Service.
We also have great case studies on different hurricanes. We’ll do this in a second once I share my screen. We do a live demo. This is hurricane Helene, a five day out forecast.
It’s an interactive case study. We have several from hurricanes, but you can see exactly for each risk score what WeatherOptics predicted five days out compared to what actually happened with real impact in terms of flooding, damage, destruction of property.
Not only that, but WeatherOptics takes this type of information, this real impact information, and is ingesting this at a very, very consistent basis to train our data to predict better for the next storm that hits. So as we collect this real impact information from roadways, from real storm damage reports, again, we’re ingesting that to improve our algorithms for both our impact risk scores and our weather modeling itself.
And I believe now we will be transitioning to Jeremy. Oh, before that, before we move on to the live demo and to our next slides here, key benefits of weather optics, just to wrap things up, we produce higher accuracy in terms of the actual weather data, that we are providing to our customers.
Are producing the impact data over the raw weather data. So AI driven intelligent risk scores that allow you to figure out what actual operations are gonna be impacted. We have a very customizable and flexible delivery, so you can access our data in a number of different ways, including with our integration within WebEOC, within the facility status bar with Juvare. And, really, most importantly, we create insights that are almost a digital twin of your operations. So we take that local infrastructure data, the data that’s important to you, and our risk scores and our data are tuned to that specific asset. So whether that’s your truck, your shipment, your location, your key hub, that is how WeatherOptics is creating forecasts and then delivering forecasts as well.
And now we’ll move over to the live demo portion of the webinar here. So I will go ahead and share my screen.
Perfect.
So this is our web based impact intelligence platform. It’s gonna show you a lot of what we just went over in the presentation here, but a live demo so you guys can get a sense of the actual software and how it works. So everything is very map based where you can see a a view of the US or you can see global view as well.
There are different forecast types that you can see.
So the first is our Nowcast forecast, which is powered by our hyper model, which we talked about earlier. These are forecasts that are meant for real time decision making, real time risk analysis, monitoring over the next six hours and what’s happening right now, how weather is going to impact your key operations. We then have our extended forecasts, which go all the way up to seven days in advance. This is much better for medium and long range forecasting. So you can play around with these different forecast types.
You can also see the different assets by which to view the weather. So right now, I’m looking at our locations. These numbers are just representing clusters of our locations that I have saved in the platform here. I can also click here and look at vehicles. So these are live trucks or emergency vehicles that I may have moving around the country and moving around the world that WeatherOptics is constantly analyzing for weather.
And lastly, on here, I have shipments. So this is our route basis, route by route kind of data that takes that origin, destination, departure time, and analyzes everything for potential weather impact both in real time and all the way up to seven days in advance.
So we’ll start here with locations, and we’ll look at our extended view here. For each of your saved locations, first of all, you can choose from a number of different map layers. So, in my presentation, I went over all of the hyper local layers that you can get. So, yes, WeatherOptics specializes in impact prediction. But if you did wanna see things like wind speed and wind gust, temperature, rainfall, radar, lightning probability, all of that information is available here as well. So all of your raw weather data layers, can find, right here in our platform.
And then you can also look at the impact risk scores that we produce. So I’ll start here with our road conditions index. Again, this is a zero to ten score of how dangerous road conditions are expected to be based off of both weather and the contextual non weather data that we ingest to create these scores. So it’s really easy for me to zoom in and see on a road by road basis where that high danger is happening.
I can do the same thing for my flood index. This this is the level of flooding.
You can see that across the country here. We have some severe weather expected a little bit later today.
So you could see that across the upper Midwest here in portions of Iowa.
We have our power outage index as well, which is a zero ten score of the chances of power going out.
There we go. You can see some scattered areas of higher power power outage probabilities. Each of these scores also have a scale, so you’re not left with just this zero to ten score. You can see exactly what that number, that numerical value actually means. That’s true for any of the risk scores here.
I can go to our life and property index next, and I can see what a six, a seven, an eight, a nine, or a ten means.
Can also click on any of these saved locations. So if I wanted to go and actually see the values, the timeline view of when these high impact events are gonna happen, I can see, you know, rainfall over time for hyper local weather. I can look at each of my impact risk scores, so I can see how road danger is going to change over time. You can see the the peak of my road danger is gonna be at one AM central time here.
I can also go if there’s any active government alerts they would show here. So this makes it super easy, again, for you to see all that information on a location by location basis.
I’ll also show here quickly our lightning probability.
Not only do we show where lightning is actually happening, but we predict the probability of that happening in the future as well. And so you can see that really nicely here. I have some lightning strikes active in parts of Iowa, and, also, I can see where those lightning strikes are expected to move over time. I can click on a given location, and see lightning probability as well, if there were to be anything to watch out for here.
There we go.
I can also change here to my satellite view if I preferred this better. Some people prefer, this sort of mapping view. So super easy for me to see where those lightning strikes or where those other weather hazards might be in regards to my critical locations.
And we’ll turn off our risk layers here.
We also have great data on wildfire events. So I can go to my wildfire spread index. I can see all active fires across the US, not only where they’re located, but I can also see where they’re expected to spread over a twenty four hour period. So this is really crucial if you’re, you know, looking to better track wildfire or fire danger. Our platform does a really good job of showing again where the fire currently is and then where it’s expected to spread over a twenty four hour period here.
We also have great data on our critical events, which is something that we went over a bit earlier in the presentation. But if I wanted to see things like hurricanes, for example, I can track, hurricane locations. I can see my spaghetti miles for hurricanes, so where they’re expected to go, their expected strength and track, a ton of information, anything necessary for, you know, where hurricanes are going to be headed, and anything adjacent to how that impact my assets. If I had assets that were in the cone of uncertainty or that were, you know, actually affecting any land locations, I’d be able to see that here. You can say I can turn on my weather event layer as well. This is more of a thirty thousand foot overview, what large scale weather events are happening, what key assets do I have that are in the location of those assets, and here’s an executive level briefing telling me what I can expect for those assets and how they’ll be impacted.
The reason I wanted to bring this up with the hurricane layer is that you can also see not only the hurricane making landfall here, but then you can see, exactly what given weather event is happening.
One second here.
Turn that back on.
So you could see both at the same time between the hurricanes and the critical events themselves.
We also have great data on earthquakes. We have great data on fires, so active fires, volcanoes. You could see those live storm damage reports as well here. So yesterday, we had severe weather that moved to the upper Midwest.
I can easily click on given locations to see the actual storm damage reports. These are thunderstorm, wind gust damages. This is hail that has been reported. So as weather events are happening, again, a one stop shop to not only see what’s expected, what’s actually taking place here.
We also have a relatively new product called our severe cast that identifies thunderstorms and will show you the risk, of of weather that those thunderstorms, those individual storms produce on a given location. So lots of different things you can see under critical events.
You can also see the power outages that happened yesterday. So you could see a couple locations here, a few counties in Minnesota, it looks like, where more than fifty percent of customers lost power. We’re taking this data directly from, the source, so we’re getting this from the actual power and utility companies. And, again, you could see across the country where power outages are currently happening updates, at a fifteen minute cadence here.
Think that should cover everything under events.
Traffic, we scrape all the five one one state websites, so no more checking individual state websites to see if there are closures or accidents. We put a one stop shop of all five one one related reports in our portal here. You can actually see still from last year, when hurricane Helene hit this area in North Carolina, the closures on roadways that are still taking place. So makes it really easy for emergency managers to see what’s actively being shut down, on the roadway or business continuity professionals, organizations.
I can see things like road status, traffic incidents.
Anything that is road or traffic related, is very easily viewable, and digestible here in our platform and in our insight portal.
Last but not least, we have our government layers. You can see that.
And very quickly here, just going over the different assets that we have, the live vehicles. I can click on any truck that I have. So if I wanna connect directly with my ELD or routing provider, I can track my vehicles. I can make assess those drivers for danger. I can also automatically send alerts to the drivers, and I can do something similar with my shipments. So not only tracking live vehicles, but tracking what route they’re going on. So I have a route here from Dallas to Charlotte, the departure time at two PM later today, I have a whole host of information on delay time of that shipment, level of driver danger, weather conditions, temperature monitoring.
And then most importantly, if there’s yellow flags here, that means we found alternative options that have a lower road risk or a faster ETA. So it helps you to optimize not only what the main route is, but are there other alternatives that could avoid high impact weather like we’re seeing here? So very clearly, you can see option a here. We run into some thunderstorms and bad weather near Birmingham. And option b, we largely avoid that bad weather information that bad weather situation, I should say.
A whole host of different things that you can do in the platform, but I think we’ll keep it there for now.
Very easy to upload your own assets that you might already have in the Juvare platform or vice versa. Take information from here, plant it into WebEOC or your facility status boards.
With that, I will pass it back over to Jeff.
Jeff, I think you’re on mute.
Yeah. I was. Thank you, Scott. I wanna take this opportunity to welcome Jeremy Reese, our special guest speaker.
Jeremy is from Geisinger Health, and he’ll spend he’ll spend a few minutes talking about real world case studies that he’s cases that he’s had in his experience. So, Jeremy, with that, I’ll turn things over to you.
Thanks, Jeff.
I’m not seeing the slide just so you’re aware. I do have it up on my side, but I’m not seeing your slide.
Let me fix that.
Okay. While you’re doing that, again, thank you for having me today. My name is Jeremy Reese. Up until about three weeks ago, I was a member of the leadership team of the Central Region Healthcare Coalition and previously worked at Geisinger Emergency Management and now back with the Geisinger team.
Still using weather optics through the health care coalition.
Here in Pennsylvania, the Central Region Healthcare Coalition is fourteen counties. It’s a diverse area.
We’re actually overlapped by three national weather service reporting offices. So a few years back around twenty seventeen after a blizzard hit the area, and there was some definitely impacts to health care across the region, The coalition leadership at the time decided we needed to find a partner that could really customize weather forecasting and impact analysis for that unique region that sees weather from the Great Lakes and weather events from the Atlantic Ocean at the same time, sometimes clashing right over the Commonwealth. So we did find WeatherOptics and partnered with them.
And we’ve also been a long term client or a long term user of Juvare through various platforms in partnership with the Pennsylvania Department of Health, which provides that to the health care preparedness program across PA for all types of health care agencies and entities to use for Internet command and situational awareness, etcetera, which we’ll talk about shortly.
How we integrate those two great products that we’ve been very pleased to use in in Pennsylvania and particularly in this region and particularly in the health system to which I’m employed, We’ll start out by accessing the portal that Scott just showed you. We’ll take a look at radar. We’ll take a look at impacts, the impact predictions. You know, if it’s a hurricane moving up from the from the Florida coast or the coastal region of the Gulf. We’ll follow that storm and see what the impacts have been. We’ll see what the impacts look like moving forward, the power outage indexes, the winds, etcetera.
We’ll then use that and some of the AI information that they have and Weather Optics to form briefings. Those briefings are distributed out to our health care members, to the c suites, their clinical leadership, logistics, and facilities infrastructure folks so that we can make some decisions on staffing, prepositioning supplies.
We are we have delved into some of the route mapping with some of our larger health systems that use hub and smokes hub and spoke supply chain models that sometimes those delivery times are two, three hours from the hub. So we will preposition pharmaceutical or blood supplies based on some of these weather analysis that we make.
We’ll also make decisions on, you know, elective surgeries, clinic closures, alternate clinic operational times, etcetera, patients that we feel might have problems getting places.
Pennsylvania is prone to a little bit of everything. We do get winter storms, obviously. We are in our vulnerable thunderstorm season right now, and then we do get the tail end of the hurricanes and the tropical storms from the south. We also have seen this summer and last summer some very significant flash flooding events in the region.
Those decisions are then made by the leadership teams in those very specialty areas or the health care incident command teams. And then we work our way to the Juvare platform. So we use Juvare EICS for the planning activities and documenting those planning activities and establishing who’s in charge.
Each facility is encouraged to create a child event in Juvare, and then they will link those events to either a regional event through the coalition or for some of our larger systems like Geisinger, we will have a corporate event where we can monitor all nine of our health care facilities, some of our hop sites and off clinic sites, etcetera, to determine how they are planning, how they respond, and is it going appropriately, or do we see any unmet needs or gaps that from a system level we have to address or be concerned about, things that might keep us up overnight during this progression of the storm.
And then the second piece of the Juvare platform that we often use is the EM resource suite.
This is where the real time situational updates come in play. Has a hospital activated their their on-site or virtual command? Have they activated their generators?
Do they have power outages? Do they have network outages that we have to be concerned with?
Are they seeing other events, you know, damages to structures, etcetera? And then, you know, for events that could create mass casualty situations, you know, road accidents during snowstorms, etcetera, We also will, you know, monitor bed availability. We’ll do bed availability polling, you know, if we do start to see an increase in the number of accidents or traumas around the region to see where we can send patients to available beds across either one health system or multiple health systems in the area.
So that’s how we’ve used these two platforms. We’ve been very pleased with the integration of the two.
Very pleased as a longtime client of both platforms, how they work to help us with preparedness, response, and recovery. So thanks for having me again.
Thank you, Jeremy. Let’s do one more poll question. This is our last one, promise, and then we’ll get on to some good stuff.
How would you describe your current approach to weather intelligence and forecasting tools?
Great. We’re getting lots of feedback. This is good.
Okay.
One more second. They’re still coming in?
K.
Great. Thank you, everyone. I’m gonna close the poll out.
We’ll turn things over to Matt Cronin. Matt, please take it away.
Alright. Thanks, Jeff. So I I got a a great question in the chat that I think helps kinda give me an intro here with what I wanna talk about, which is the integration. So the question was, is this program built in WebEOC, or is this a separate platform?
It’s both of those things. Right? So this slide kinda talks to to that. Right? So the last bullet, access to the insights portal, that was what Scott showed earlier.
So as part of kind of this solution, you do get access to the insight portal for kind of that, you know, comprehensive access to all the tools and capabilities over there. But, obviously, a key part of this is integrating with WebEOC, and that’s done in a couple different ways. So in the first bullet here, we feed the data from WeatherOptics into our facility status board. So, in our standard facility status board, you have all your facilities set up, and then that can integrate with, WeatherOptics to give some, your, you know, your potential weather impacts using the, risk prediction, using a lot of the AI and machine learning and and other things that, Scott mentioned earlier.
But I’ll show that in in a moment here, so I’m just, leaning up to that. The other part of that is, map layers. So a lot of this data, WeatherOptics provides in GIS layers, those layers can be shared. If you are using, ArcGIS already, it can feed into ArcGIS.
It can also obviously, since we have GIS capabilities in WebEOC, we can also pull that data into WebEOC very easily as as well. So it it’s those three things. Right? It’s access to, the insights portal, weather optics system directly, integration with our facility status board, and then the third thing is, is map layers.
I I would say the fourth one would be an optional thing where I saw another question about, can this integrate with the incident action plan?
So we we’d have to have a discussion of that. My my next question would be, how would you want that to be integrated? The the answer is yes. It can we can integrate WeatherOptics with unique status boards, but that would be more of a combination of would include some professional services or some, you know, services to get that done.
But the the goal with a lot of this is for turnkey solutions, and that’s really what we’re focused on today. So rather than saying the slide, I’m gonna go ahead and share my screen and kinda walk you through some of these things.
Alright. So we’re we’re in we’re in WSC. If if you’re not familiar with what I’m seeing here what you’re seeing here in terms of the look and feel, this is Nexus. If you don’t know what Nexus is, we’d love to give you a demo and get you caught up because we’ve we’ve come a long way in terms of these home pages and the ability to quickly access your your tools and capabilities such as your facilities with weather optics baked into that.
So when I open that up, that brings me right into the insights view. And this is gonna show you all your facilities and give you some some visibility into the impacts to facilities. In this case, we used airports because, you know, they’re spread throughout the US, and so it’s an easy kind of set of facilities to use for for demonstration purposes. Right?
So we have a lot of airports out the US.
It’s a lot of a lot of ways. You can also filter down to the facilities that are gonna have potential weather impacts. And what that’s gonna do is that’s gonna filter down just to those facilities that we’re anticipating within the next seventy two hours significant impacts to those locations. And so with that, you can see the map is filtered, and you also have the the table down here is filtered.
You also see the four different risk indexes, roads, business disruption, flood, power, and you can see the numbers are the risk scores. And then those numbers, you hover over them, provide a description of what you can anticipate in terms of that road danger or or business disruption. You can also click on the record and get the slide out, which would show you, you know, all the details about that location as well as more granular information. So one hour out, two hours out, up to six hours out, and then, you know, more generally, next twenty four hours, it looks like this this risk score of six is maybe with a twenty four to forty eight hours.
And, again, I can hover over that, and that of what can what can I anticipate from that? You also have this graph up here. I could turn off different indexes by clicking on them. There’s a legend I can show, which will show the, you know, the level of danger based on the number.
And as I hover over this, it will give me kind of a a description once again of of those definitions for the various levels for these various indexes here. And so, again, this is the facility status board integrated with WeatherOptics. You can see that all data updated within the last and providing the latest risk predict prediction information. With this, you also can set up the using the alerting engine that sits, you know, behind WebEOC, you can set up rules so that alerts that you received.
Hopefully, you can see this. I’ll just slide my my email here, and you can see it’s been a little slow. Some example emails that were generated to show that, you know, Miami International Airport is expecting, you know, road condition of six point one within the next, you know, seventy two hours, business disruption of three point eight. And then if I wanna view that facility, I can click that link and be taken right into into WebEOC. So this will automate, so you don’t always have to be in the system. You can receive these alerts that will tell you that, you know, something is, you know, anticipated, and then you can come to the system either in WebEOC or in WeatherOptics to get more information.
Wanna kinda move on from the facility status board and talk about a couple other ways this information is integrated.
These GIS layers, Scott showed a lot of this information as in his demo.
Think we’re gonna be from, you know, power outages to you can see, you know, volcanoes, fires. You can see the fires. You can see due to all of these.
I can see the legend less important for that one since they’re all the same. But if we go into, like, storm reports, this will show you what, you know, what here, you can see the the underlying detail behind that. So this is a flat We got a tornado report here. So all this information is coming through from the other feeding into the way you see, and and then you can visualize it in here.
So a lot of these different layers are available as well as one additional map. I’ll show you. You can you can, again, add these layers to any number of maps. One that is pretty cool is the critical weather events layer.
And so this is a worldwide map that will be the weather areas. And you can click those areas, and it will show you, you know, you know, what type of event is it. It provides a good kind of executive level briefing of what to expect from this event.
And then as you scroll down, you can see the immense amount of different information in terms of wind, you know, index information, you know, what we can expect in terms of range, just all sorts of information fed into the pop up here. And, again, this could be overlaid with any other information that that lives lives in WebUC. So your, you know, your shelters or your facilities or your where where missions are going on, this can be overlaid as necessary. So, yeah, just wanna kinda show the different ways that WeatherOptics can be integrated with both the facility status board and these various GIS layers.
But I’ll go ahead and stop sharing my screen and turn it back over to Jeff.
Thank you, Matt. Much appreciated.
Let me get my screen back to where it belongs.
Okay. Let’s talk about questions. I saw a few questions pop up in the chat. Let me just get that those questions up, and I’ll put them out to the group.
Let’s see.
Matt, you already answered one of the one of the first questions was that, is this program built into WebEOC? It is both separate platform and built right into WebEOC, so the answer was both. Matt handled that one.
Let’s see. Next question.
What unique forecasting capabilities does weather optics bring to WebEOC? That one’s gonna be for you, Scott.
Yeah. It’s a great question. I think the unique forecasting capabilities are really around the impact data that we provide. Right? So, the risk scoring that we provide is pretty unique to WeatherOptics and the fact that we are accounting for local infrastructure in this nonweather data. You know, we’re helping to answer that crucial question of how does one inch of snow in Chicago, you know, make a difference between that and and Dallas. Right?
Same amount of snow, but two totally different impacts in different locations because that nonweather data is so crucial. So all of our risk scores were able to understand how susceptible a given location is to certain conditions, and and I think that’s a big part of the uniqueness that we bring to the the WebEOC platform.
Excellent. Thanks, Scott. Another one for you, Scott, I believe, and this may need more discussion.
Is there additional cost to WebEOC? And if so, how much is it? Has the state purchased, and do they, if they do, will counties be able to utilize it?
Yeah. That might just just require more discussion. It it is an additional cost to to purchase weather optics as an add on application.
And I guess it depends on what state is specifically being talked about here. But, yeah, probably a good question for offline for, you know, the group to discuss.
Next question is about risks risk scoring, if I can say that word. Can you describe the matrix details that is built in in in built that considers local risks? Sorry. That’s not clear. Can you describe the matrix details that is built that considers local risks?
Yeah. Absolutely. We have really good documentation on this, so we can pass along how, like, the specifics of the matrix and what is actually being accounted for in the given local risks. Again, I listed some of them that that we are looking at, like distance from river and slope of roadway and tree height and density and historical power outage data, but we can totally provide information on actual the scoring itself and how we determine what’s a three versus a seven versus a ten.
Yeah. We can definitely do that.
Okay. Can you say a little more about damage prediction? If I heard correctly, based on predicted weather, you give some kind of score on how it may impact our facilities. Does it take into account things like wood structure versus cinder block or similar?
It’s a great question. It’s super granular. It doesn’t necessarily take into account the specific structure of a given facility, though, although that could be a really interesting input.
If you, as an end user, were to have information on the structure of certain facilities or if we had a way of gathering that data, we could potentially account for that in the risk scoring. Right? Certain structures would obviously be more susceptible to, let’s say, wind gusts over seventy or seventy five. And so we do a lot of work with, like, the nonweather component of that, but not specifically what the structure is built out of. Although, it’s super interesting idea that I, I would say is possible if we have the right information.
K. Looks like the last question. This is pretty extensive. How well will this fit into smaller towns or cities?
It fits well into, you know, local local regions as well, local locations. It it it goes down to a three kilometer by three kilometer granularity. So, that is a global grid where everything is broken down into basically a three kilometer chunks. We have some products that work even within three kilometers itself, so you should be getting different data within, you know, smaller towns or cities, for sure, as well as more regional data available.
And we’ve got a few more, Scott. Can you geofence several locations just to get alerts for those areas?
Yes. If you wanted to geofence or or group several locations to just get alerts for a certain region, you could absolutely do that. You could also set different thresholds for different groups or different locations. So maybe, you know, some you wanna set a threshold of a seven.
Or, yeah, if you wanna group things together, that’s totally possible. Everything is pretty flexible.
And then I I see there’s also a question about where we’re pulling data sources from. Yes. Stream gauges, river gauges, any information that we can get. There’s a number of different ones.
I mean, some of it comes directly from NOAA. Some of it comes from, USGS. Some of it comes from available data on ArcGIS. Some of it is our own proprietary sources where we’re looking at weather station data, some of its camera data, and local road status from five on one state website.
So there’s a a ton of different sources that we’re pulling both weather and non weather data from. And, again, we have that available in documentation if if, folks are looking for, you know, that specific information.
Okay. Last question. How do you define forecast error?
Forecast error, I believe, is basically how far off, you know, we were from the actual prediction from the ground truth compared to both the h triple r model and the hyper model. So we were collecting ground truth data from, you know, across the country or from specific points and then comparing it how far off it was to what actually occurred for for a given location or a given region. And we can give you specifics for those two charts that we put up on the hyper versus h triple r model, we can give you, specifics for how the the error was calculated.
Excellent. Thank you.
Jeez. They keep coming. One more.
From San Francisco Bay Area, although weather is not an issue, we realize it’s a timing issue for it to be useful. But have you tapped into any early earthquake warning systems?
It’s a good question. Currently, I think we’re just using, some of the the the basic, data from USGS for the the earthquake data, Although, we’re always open to tapping into new types of warning systems. So, if there is information that gives, you know, a a heads up, we have heard about some of those early warning systems. I don’t know how well they’re verified or tested, but we would be open if it’s a source that’s currently being used by, you know, an end prospect or potential customer for from us.
So, yeah, we would be open to that, but currently, I think we’re just using the basics.
I also know, Jeff, that there’s a lot of questions coming in directly to the q and a itself. So I I I wanna make sure that those people, you know, maybe we can I I don’t know if we’re going to the top of the hour here, but if we can’t get to all the questions, maybe we can, you know, follow-up with some of these folks? But beyond just the webinar chat, I know there’s a q and a section that, has a lot of questions coming in.
Okay. And we can answer those, independently, offline after the event. We’ll we’ll respond directly.
Yeah. Okay. We have some future webinars coming up. We welcome you to join us. We’re trying to do one of these every six weeks, so, we’re gonna put together a flood detection webinar, fleet tracking webinar, and a drone detection webinar.
All things are, you know, pretty timely, and we look forward to having you join us for those. So look look for those invitations. Look for us on LinkedIn with these announcements, and we’ll be hold hosting more of these going forward. Thank you all for attending. Have a great day.
