TRANSCRIPT:

TRANSCRIPT:

Welcome, everyone. Thank you for joining today.

Welcome to our webinar called enhancing wildfire response with WebEOC and SenseNet.

Before we begin, just a few housekeeping items. Today’s session is being recorded and will be shared with all registrants after the event.

All attendees are muted by default to minimize background noise.

Submit your questions anytime via the q and a panel. We’ll address them as time allows. And if we don’t get to some questions, we’ll be, circling back afterwards, and answer them directly.

If you’re having any technical issues, try refreshing your browser or maybe leaving and rejoining the session.

Today’s session will run about forty-five minutes and, we’ll send out a survey after the presentation.

And we welcome your feedback on that survey.

Today’s agenda, I’ll introduce today’s speakers.

We’ll get an introduction to sense that our new partner here at Jabari.

We’ll do an overview of since that’s wildfire detection technology.

We’ll hear some real-world use cases with Vernon BC Fire Chief David Lind.

We’ll get the key benefits of using SenseNet for wildfire detection and response.

We’ll talk about the integration of SenseNet with WebEOC.

Matt Cronin will do a live demonstration of our WebEOC wildfire board.

We’ll field any questions that come up. We’ll talk about our future webinars, and I’ll tell you about how to learn more.

Today’s speakers, Andrew DeStefano, is VP of sales, business development, and alliances at SenseNet.

David Lind is Fire Chief, Vernon, BC.

Matt Cronin is VP of solutions engineering here at Juvare.

And I’m Jeff Berkovich, director of partnerships at Juvare.

With that, I’ll turn things over to, to Andrew. Andrew, take it away.

Thank you, Jeff.

Appreciate you having me today.

And also, a big, thanks to the Juvare team for helping us, facilitate this webinar.

So, I’m here to talk to, about the SenseNet, early wildfire detection and management platform.

So, what I wanted to do is, you know, everyone’s sort of heard the old saying that a picture is worth, a thousand words. Well, I have, some drone footage, which I’d like to show you, which I believe is worth ten thousand words.

So, so this here is, wanted to show you a deployment, that we actually did in Vancouver.

This is Predator Ridge, British Columbia.

This deployment was done, we, it deployed our wildfire cameras on this, cell tower.

This is through one of our strategic partners with a telecom company in Canada called Rogers.

What I’m showing you here is the, some drone footage that was taken the day, we did the installation. This was, April of last year.

And what you can see, is the operator who’s, we’re in the process or, he was in the process of configuring the cameras at this point in time.

Just showing you the sort of capabilities of the of the wildfire cameras.

These are AI based, cameras that can scan the landscape twenty-four seven, looking for searching for, plumes of smoke.

Whether it’s, daytime or nighttime, we you know, any smoke plume is detected, will be identified by our wildfire cameras and our AI based platform.

So, what this is an automated system. As I said earlier, we’re just showing you, the operator is just doing final configuration.

But what, what took place on this day is that we actually, or the platform actually identified the very small, very first smoke, incident.

And, what you’re seeing there is, the operator just zooming in to that specific, location, you know, gathering real time, situational awareness as to what’s happening on the ground.

In the background, the platform is, is determining the latitude and longitude of that smoke incident. And once that information is, is compiled, then, the platform will automatically send an either a text message or an email to the local fire department, or the wildfire, and or the local wildfire agency.

We also have some private customers, private enterprises using our solution.

They can be notified directly as well. Sometimes they have their own fire crews. And, essentially, we’re providing the that first, you know, that that quick, identification, of that fire or smoke incident and, giving that sharing that information with the, the proper authorities in order to facilitate a quick response.

Okay. Thanks. Thank you, Jeff. Okay. So that was one component, the wildfire cameras. Now, that’s just the one component of the solution. We have it’s a fully integrated, wildfire monitoring platform.

And so, the smoke detection cameras, you know, I’ll provide a little bit more detail about them. They are three hundred sixty-degree high definition, panoramic cameras, which are, like I said, are constantly scanning the landscape for smoke incidents.

The detection range of the cameras is about fifty kilometers, which is, roughly thirty miles.

And, fully autonomous, as I said earlier, with the ability to, you know, for example, if the fire department or, you know, private customer would like to take, remote control of those cameras, they can definitely do that as well.

Okay.

The second component of the solution are ground sensors.

Now the sensors are typically installed on the tree line. And what they’re doing is they they’re scanning, for anomalies and gases. Okay? So, they’re, very highly, you know, sensitive, sensors built in there. We will, collect data or these sensors will collect data on a regular basis.

And we’re looking at things such as, you know, carbon dioxide levels, carbon monoxide levels, nitrous oxide levels, just to name a few.

Because we know that, you know, microclimates are very important when it comes to wildfires. We’re also, measuring the local temperature, humidity, moisture levels, as well as, in a particulate matter. So, two point five, five, and ten. And we’re providing, we provide air quality monitoring as well. K. So when we have the combination of sensors and smoke detection cameras deployed, they are integrated. So, they, they work together, and, the sensors typically will detect, smoke, in or fire into smoldering stages.

Once an alert is, is raised there by its either, you know, one sensor or multiple sensors, what will happen is that the, a platform, that alert goes back to a wildfire monitoring platform. The smoke detection cameras will zoom into that specific location and take some photos.

The platform will triangulate the GPS coordinates of that smoke incident, and then we’ll notify, the fire department, and wild wildfire agency as well.

All that sort of all the information, all the insights, it is housed within the monitoring platform.

And this is also where we have, another component of the solution is the satellite imagery. We do have integration, to it’s about twenty satellite feeds that can, near real time satellite feeds that that are also integrated into our platform.

Within the wildfire monitoring platform, that’s also, there we have the capabilities, to, predict, you know, wildfire spread. And its a, it’s specific, model that SenseNet has developed, and we’ll get into that, in a few minutes.

But this is, you know, as I said, it’s a comprehensive early wildfire detection platform where we’ve taken, multiple technologies and sort of embedded them all into one platform.

Next slide, please. Okay. Now, you know, we could speak to, or I could speak to sort of the system and the technology for hours, but what I’d, what I’d really like to do is introduce some real world, use cases.

And, in order to do that, we’ve invited, Chief Lind, who is the director of fire rescue services for the city of Vernon.

The sense that team and I have been, working with Chief Lind for I think it’s been, well, about four years now. And, Chief Lind, he brings over three decades of experience in fire and emergency medical services.

He’s dedicated his career to protecting communities across Manitoba, Alberta, and British Columbia.

He started his journey in nineteen ninety-one, where he served in various capacities, including, being a firefighter, rescuer, a train, trainer and safety officer, instructor, evaluator, deputy chief, and fire chief.

Chief Lind’s experience includes the management of large-scale emergency events, such as floods and wildfires.

He’s known for his strategic thinking and his ability to connect people and agencies.

And David has consistently, improved service delivery and is elevated fire rescue services throughout his career.

So, his willingness to tackle difficult tasks and navigate turbulent times has earned him a reputation as a resilient and an innovative leader.

So, without further ado, I’d like to introduce chief Lind, who will talk a little bit about his experience, you know, as a fire chief for the city of Vernon and also, you know, his experience with the SenseNet solution.

Thank you so much for that introduction.

I I’m, very grateful for the, for the time here today, to talk about Vernon’s experience with SenseNet and, kind of share a little bit about our story. I’ve been with the city now for, nine years, and, we are, located in the Okanagan.

We about ninety-five square kilometers of, of land that our department, protects, from three fire stations. And so quite a spread out, geography.

Lots of, wildland interface areas.

You know, the city, Vernon was, fortunate, to been introduced to SenseNet at a time when the company had completed its initial trials and field testing. They had done some early work in Williams Lake with positive results, and they were at a point where they were looking to carry on and do a larger scale, testing and evaluation proofing of, of the system.

And we found ourselves in the right place at the right time.

Vernon had this wild LAN interface risk, that, worked really well for, brown truthing, the project to the system.

And, you know, for a lot of years, Vernon City Council, has advocated for fuel treatments to reduce risk within the city, and a lot of that work had been pretty innovative in itself, really forward thinking in approaches to try and address this, these risks within the community.

You know? So, it was very reasonable to think that our mayor and council would be supportive of the trial. And when I first met, Ahmed, SenseNet’s founder, I think it was in the fall of twenty-one, and the Okanagan had just experienced the White Rock Lake Fire.

That that fire, for those who, aren’t familiar, it burned pretty much all the way from Kamloops to Vernon, and it covered eight hundred and thirty-three square kilometers.

Portions of the city of Vernon had been put on evacuation alert during the event, and for a short time, there was a recommendation to evacuate the entire city. And the only thing that, that stopped that evacuation was a very last-minute change in, winds and temperature and rain at the same time. And so, at that point, the city of Vernon came as close to, executing a full-scale evacuation as a community can without, without actually having to do it. We, you know, avoided it at the last possible minute.

So, think about that for a minute. Imagine not only, evacuating, the able-bodied population, but also the hospital, care homes, seniors, group homes, the unhoused, basically everyone and their pets. And in the case of some of the ranching and, those types of, agricultural activities in the city, even, livestock and animals.

So, just a monumental task. And so needed needless to say in in twenty-one when presented the opportunity, to participate in this, this, trial, it was a federally supportive, innovative, trial with SenseNet’s emergent technology for, wildfire, early detection. They were super supportive.

So, we had a couple years of, installation, testing, refining, and then retesting the system.

And during that time, I found the public was super interested in the project, in the technology, and encouraged.

It was very good to be seen to be doing something proactive, to reduce or, at least in in some way address, the community’s, wildfire risk.

And the interest and excitement around the early wildfire detection and monitoring, worked to bring those in the area, more closely together around the topic.

As the system started to prove itself out early on, other neighboring governing bodies decided to participate in the trials, mounting cameras and sensors in their communities. And it worked really well. Basically, their cameras could see across the lake into Vernon, and Vernon could see across the lake, into their communities, which, in in wildfire terms, if you can see something coming, from a way off, that’s always a very good thing.

One of the prominent developers this was unexpected, but, or at least, from my perspective, unexpected. But one of the really prominent developers in the city, who whose, development is located in our, wildland interface invested in additional sensors and cameras around their property.

And that, drastically increased, our ability or the system’s ability, all on all on its own. And at the same time, already mentioned, I think, is the utility companies, some of the cell phone, providers, and I understand even rail systems are looking at, implementing the technology. So, very powerful if a community has this, system in place and then, others, in the area are adding to the system, it really, helps with that early detection, basically blanketing the community.

So, the experience of the government, private landowners, utility companies, and, and others having conversations and taking action independently and cooperatively, both at the same time, has been incredibly encouraging for me. So much of the work in addressing risk, around wildfire in local government has been, boundary, bound, I guess, search for a better word, but, locked into, who has authority, who has jurisdiction, geographical lines on the map. And we know that the fires, don’t really respect any geographical boundaries.

So, I’d like to talk about the system itself, and share, information, and how it shares information with the end users. And so, in the in the city of Vernon, we have, monitors, displaying the SenseNet dashboard, in each of our fire halls and in our emergency operation center.

And we have, notifications being pushed also to iPads and cell phones, individual, users. So, my deputy chiefs and I, each get, directly messaged when SenseNet picks up a fire in the community.

And then so when we receive that notification, we can look at the dashboard to see where the sensor and the cameras are located, and we get that, longitude and latitude, from the program as well.

And, also, we get sent a photo, of the, of the fire in the area, the plume. And, in the photo, there’s a little red box around the, around the fire.

It makes it very clear. And, then if we want to, we can go back to the manual cameras and actually zoom in and get some real live feeds and have an assessment of what’s going on there, before we even, before we even turn a wheel.

So today, the system is reliably reporting fires in the community.

I get, reports on a regular basis.

And we’re working through this, is that at this time of year, fires are actually permitted in the city. The, the permit system in Vernon has just shut down for the year, but our neighboring, municipalities, still are issuing permits, for, some activities, some burning.

So, so in a single day, there can be, quite a few controlled fires, that are visible to the system, within the Vernon area. And during these times, we’re not as concerned with, that activity. We’re actually encouraging it. We’re trying to reduce the risk on the on the, on the landscape, getting rid of some of the agricultural material that’s built up over the season or, thinning bush and that type of thing.

So, I mean, at this time of year, the moisture and the vegetation is good. Humidity in the air is good. Temperatures are really cool. And in short, the fires don’t really grow or spread quickly in these conditions.

So, what we’re looking and working to figure out is how to adapt our fire permit process to ensure the SenseNet AI knows about permitted fires at this time of year in these, less risky conditions.

And what we are finding is that once the fire bans go into place, so once the conditions are changing, it’s hot, it’s dry, and conditions are optimal for rapid fire spread, then then we’ll be able to pick up, any, new fire activity, really quickly and, take action on that. So, an excellent value add for us, has been the avail the ability to share information with, BC wildfires and, others in the area so we can actually share what we know and what we’re learning, from the system.

There are a couple other uses for the information that we’re still trying to unpack as the end user as we’re trying to, so we have this new tool and this new level of information that we haven’t had in the past. And we’re trying to unpack how do we use this best? How do we, maximize the benefit?

And so, we’re looking at, monitoring some of the fire activity in our urban centers.

We’re practicing with our emergency operation center, using the fire modeling, aspect of the program or the system. And, also, we’re having conversations with our bylaw enforcement department.

Excuse me.

In those urban areas, where fires are occurring with a regular frequency, we’re planning to temporarily install sensors and, also install a camera in our downtown city core. This wasn’t the original intent, but, another large Okanagan city, has used the technology in this way, and they’ve had very good results. So, that’s something we should probably have, underway in the next, month or so.

And, our emergency operations team, as I mentioned before, has been, trying to figure out, hey. How can we use this, fire forecasting, modeling, to help us with evacuation planning?

It’s going to give us, decision points. Okay. When do which neighborhoods do we evacuate? When do we evacuate them?

And where should we, concentrate some of our firefighting efforts, to protect those evacuation routes?

So, and as I’ve mentioned earlier, during the fire ban periods, our, bylaw team with fire services, can use the system to actually enforce our no burning, policies, to help, avoid some human caused fires.

So, just recently, the city’s entered into, a longer-term contract with SenseNet, for maintenance of the system, and for continued improvement. It’s, improving all the time. And I I’m so encouraged by the use of this, technology, to help, tackle the wildfire risk in our community. And, like I said earlier, it really is bringing people together around, a practical system.

There’s actually action we can take, and it’s helping to reduce the impacts of wildfire within the city of Vernon.

Thank you.

Chief Flynn, thank you very much for your help today in in presenting your experience with SenseNet. I’ll turn things back over to Andrew to continue.

Yes. Thank you, Chief Lind, for taking, time out of your, you know, valuable time out of your day to speak to us about your experience.

What I wanted to do is, you know, put together just a sort of a snapshot of the, of the work that that that we’ve done, in the city of Vernon, along with Chief Lind and his, and his team.

So, we’ve been, it’s I think it’s, almost four years now that, since that has been installed in the, you know, originally as a as a pilot, and now as a, you know, a full-blown commercial deployment.

So over that period of time, you know, I’m pleased to say that there have been zero wildfire outbreaks, in the city of Vernon.

And what you can see there is, in the they in that, map there that that green, dot, you know, with the white check mark, that represents just the city of Vernon.

We’re looking at a population of about eighty thousand people.

The area is surrounded by; it’s over a million acres or four hundred thousand hectares of forested land.

And, what you see in the, in the graphic there, those little, orange dots actually represent all the historical fires, in the in the, surrounding communities.

So, the sense net platform detected two seventeen fires, and, with the help of chief Landon and his fire crew, we’re able to mitigate those fires, in the early stages.

And the average detection time, was about three minutes.

So, I just wanted to provide sort of a snapshot because this is sort of, one of our longest, running deployments.

And, also wanted to say that, you know, I’m not saying that sense that is a silver bullet by any by any means.

Sense that is a tool. Think of it as a tool that can, be used, in another tool that can be used in a firefighter’s toolkit.

And along with the, the platform and, you know, proper fuel mitigation efforts, you know, as well as there’s a program in in British Columbia called FireSmart where, you know, the, Chief Lind and his team work very closely with the community to fireproof their homes. When you have it’s, all of these sorts of collaborative efforts that are put in place and, you know, along with the early wildfire detection piece, and the, and the quick response, this is sort of what helps deliver, you know, these, these results.

Next slide, Jeff.

I’d like to spend, just a few minutes talking about the real time, wildfire tracking, capabilities of our platform.

This is sort of part of the, you know, what I call the secret sauce, of the solution.

We can provide we will you know, within the platform itself, you’ll be able to, you’ll be able to see, or visualize the current fire perimeter.

And this this will display information such as, you know, you’ll see the latest updates on, how quickly the fire is spreading, the intensity of the fire.

We layer in historical wildfire, analysis as well, which basically will allow you to track, you know, help track the fire from the ignition to its current state, helping also to basically understand different patterns and how the fire could, potentially impact the community.

And last but not least, we have our advanced prediction model. This is a model that’s proprietary to SenseNet.

SenseNet has twenty-one patents to date, on the solution.

And the prediction model will help, basically project the FHIR’s path. You know, it could be over the next seven days, over the next fifteen-, twenty-, or thirty-minute intervals. That’s all configurable within the platform.

We take into consideration over twenty different factors, and that’s everything from the sensor, the data that’s being collected by the sensors.

We look at, different information such as the wind speed, the wind direction, the vegetation type, the different fuel types that that are available in the area. And we’ve put together, within the platform, you can, you can run a fire risk simulation model, which is sort of you see, some pictures there just, or screenshots, bottom left and top right of what a simulation would look like.

And, again, this is something that, we can go into, detail.

If there’s, further interest, we can give a live, demo of the platform and go into, into all these, capabilities, in detail.

Next slide, Jeff.

Okay.

I just wanted to talk a little bit about sort of, the different reports that that, can be produced within the platform.

So, this is, you know, the very first one is the daily, wildfire risk heat maps. So, it’s something that, we use, three milli three-meter, resolution satellite imagery to produce the daily heat maps. Again, this takes into consideration all the information, all the data that we’ve compiled, within the platform.

The historical analysis, which I mentioned earlier, can also be used to set up sort of, buffer zones or boundaries.

And those, essentially using past wildfire events or the information from past wildfire events, analyzing sort of the fire, risk in in those in that area of that community, re helping to refine our risk calculations and, you know, work towards, mitigating and, building up preventative strategies.

We look at the local threats to infrastructure and, perform community risk analysis.

That’s all done to sort of assess the wildfire threats and, and be proactive in terms of, you know, determining what could happen, based not only on historical information, but on also on current, current conditions.

Lastly, since then has developed an ember, spread mapping or, that’s essentially, we use ten-meter resolution.

And what that does is it can track the movement of embers. And we can help sort of, visualize and predict what, what, infrastructure is at risk or what, what communities are at risk by developing the ember spread model. And an example is just one, you know, one you’re seeing there, to your right. That’s an ember risk map that was, created for, British Columbia.

So, in essence, you know, we’re looking at, you know, using all the information, as I said earlier, compiled by everything from the sensors to the wildfire cameras, the real time, you know, situational awareness to help with evacuations.

You know, every if sort of every piece of information that’s available even, from, real near real time satellite imagery, to help sort of build that comprehensive, model, which will provide sort of the, you know, the, critical information that’s needed by fire departments, wildfire agencies, and, you know, private agencies, to help deal with, you know, to keep the identify the fires or the smoke, incidents early on and, you know, ensure that there’s, you know, a quick response and keep those fires small and, you know, ensure that they don’t get a they don’t become catastrophic.

Okay. Andrew, thank you very much for that.

Next, let’s turn over to Matt Cronin to talk more about the WebEOC SenseNet integration. Matt?

Alright. Thanks, Jeff. So yeah. So, obviously, this is a very powerful platform, that we’ve integrated with.

How we’ve integrated with is through our, what we call JX connectors, which are, you know, standard ways that we integrate with third party applications. We’ve we have many of these, and we’re creating more really each month.

This integration brings in that powerful wildfire sensor data into WebEOC to really help teams that are, in WebEOC be able to make decisions, faster, be more informed, and just have that that information at their fingertips. But let’s go ahead and dive into it and look a little closer at that. So, I’m going to go ahead and share my screen really quick.

Jeff, can you confirm you can see my screen?

Not yet, Matt.

No? Andrew?

I can see it, Matt.

Okay. Great. So, so what we’re looking at here is WebEOC Nexus, latest version of WebEOC.

In this case, I have a number of our different integrations we have, but let’s go ahead and look at our wildfire detection with SenseNet.

So right when I come in, typically, I’ll be brought into the sensor screen. And so, this is going to show you all of the sensors that are, you know, associated with the account that you would have, in SenseNet. And you can see as I drill in, I can interact with this map. I can, zoom to a particular sensor location, from the, the table here. I can also drill into a particular sensor and see all the details about it, the temperature, the humidity, the air quality information.

Each of these, you know, different, items, kind of are just defined here for users that, you know, might not be familiar, with what some of these things, you know, mean.

And, you know, air quality index, all of that is being, captured by the sensors and then being fed, you know, pretty much real time, essentially every minute or a few minutes depending on how that’s configured, into the WebEOC board. So here I have all my various sensors. You can see in some cases that certain sensors might have different information that they’re capturing, just because there’s, you know, different sensors that can, capture different information. And whatever it’s capturing, this is dynamic, in a sense that it will bring in all of that detail into WebEOC, for visibility.

Just some other things here to walk through what we have. We also have all the cameras. So, you’re probably, you know, you’re probably going to have a lot more sensors than you are, cameras just because you don’t need as many cameras as you would need, sensors to capture the data. So, in this particular area, we have three different sensors, one up here in the north and then two down here. And each of those cameras, if I scroll down here, you can kind of see a thumbnail photo. If I drill into that, I can see other, associated, you know, additional thumbnails, of that information of those cameras. You can also see the last time that the smoke was detected, from that particular location.

As, we heard earlier, the images will have a little square that that kind of identifies, more closely where that’s coming from. I can also go to a full screen view if I want to look at the information in more of a full screen view. I can see again where that camera is on the map here. So, there’s a lot of different, options to pull up, and see the data that’s being captured in in SenseNet but then coming into WebEOC.

A few other areas with some useful information we’re pulling over. Alerts. So, Andrew mentioned that there’s a lot of different alerts being captured that’s going to capture the type of alert it is, what sort of information, you know, what’s happening, where it’s happening, whether it’s confirmed, smoke, whether it’s just snapshot report. And these alerts can also trigger, alerts in since that can send alerts, and WebEOC can also send alerts.

You know, so it could pull in all that information about that alert. It can give you links to the different maps or the app to see more detailed information. And, again, just make sure that, the folks that need this information are able to quickly be informed about this information through alerts, whether it be from SenseNet or WebEOC.

You got both options available there.

You also have your locations. So, they’ll basically be locations that we’re, monitoring with it which in this case is that Predator, Ridge Resort area. So, you kind of see the area that we’re actively monitoring.

And then just finally, just a dashboard just to summarize, you know, how many sensors do we have, what’s the average temperature, how many cameras do we have, what sort of, alerts have we received, recent alerts, smoke detected within the last seventy-two hours, average CO, average humidity. You can, expand some of these other, you know, charts here to see particular matter averages or gas measurements.

And all of this information is just here right at your fingertips, where you can just see the details, drill into the detail here. And then if you really want more detailed capabilities, obviously, you have the SenseNet application that you can log into for, the full set of bells and whistles. So, and we’ll continue to likely expand this integration as we, get feedback from our early adopter clients on, what sort of features and capabilities they want to also bring into WebEOC from sense that to, make more informed decisions quickly.

So that’s all I have. Let me turn it, back over, to the group for, continued presentation.

Hey, Matt. If you would just leave your screen, up there. We have a couple of questions.

And maybe that’ll help us along with some of these.

One question we have is, how will I know how many sensors and cameras I will need?

Andrew, can you field that one?

Yeah. Definitely. That’s a great question. So, what we’ll do is we’ll actually, you know, take a look at the, the area in question. Right? We will, do some analysis.

We’ll determine, you know, based on sort of the because every community is unique. Right? We will determine, you know, what combination of sensors and wildfire cameras would be required, to cover the area. Right? If whether it’s a small community or a large community. So, you know, and that that could range from, you know, it made for a small community to maybe just twenty sensors.

Typically, one gateway for the connectivity, and one wildfire camera would suffice, for the for larger deployments such as, in, in Vernon there. We have, you know, over a hundred sensors and five wildfire cameras. So just depends on your community, but we would, we’d work very closely with you to understand your needs and, put together a proposal for you.

Fantastic. Thanks. Another question. How long does it take from purchase to implementation of the integrated solution?

You’re looking at about four weeks, from the time the contract is signed, to, full deployment.

Fantastic. Okay.

And looks like the last question so far, how is support handled? And I’ll fill this with myself.

So, Jabari always handles the first level first line of support. If you have a question or a problem with the integration or with the way sense that it’s functioning, you will call your standard Jabari support line, and we will take care of the support from there. We’ll get sense that involved if need be. But we can usually field a lot of those questions right up front.

Okay. I think that’s what we have for questions. Let me share my screen back again.

Here you go. I can go to the end of this.

Okay.

So, if you all did the questions, thanks for those. So, we have some future webinars coming up. I’d like to invite you all to those. We’re going to be doing webinars on fleet tracking, flood monitoring, weather intelligence, lots of different webinars over the next, coming year.

So please, keep an eye out for those, and we’d love to have you join us.

To learn more about anything you’ve heard today, please use these connections. Reach out to me or to Andrew. Hamid Nore is the CEO of sense that he is also on the call. He’s been listening.

Please feel free to use any of these connections to learn more information about anything you’ve heard today.

That is, it. Thank you all for attending. We appreciate your participation. We will be sending you a follow-up, survey just to get your feedback. Thank you very much.