Catch It Before It Spreads: The Future of Wildfire Detection with LoRaWAN

Speaker: 00:00:05

Welcome to

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the business of LoRaWAN,

where we dive into this long range,

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low power, wide area network

and its impact on your bottom line,

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the latest sensors and proven real world

solutions.

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I'm your host, Nik Hawks.

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Since 2020,

when I stumbled into LoRaWAN via helium

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while hunting for a lost paraglider,

I've helped thousands understand

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how it works and how to use it,

and I'm psyched to do the same for you.

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I've installed everything

from soil sensors

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to weather stations to retail foot

traffic counters.

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Coming to the conclusion

that LoRaWAN is rad,

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so I built the only show on the internet

fully dedicated to unlocking its potential

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for your business.

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Let's dig in.

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Today I'm joined by Vasya

Tremsin, the founder and CEO of Torch

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Sensors, a wildfire detection company

using LoRaWAN connected smart sensors

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to catch fires at the spark, often

within three minutes of ignition.

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Thus, his story is wild in the best way.

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He came up with the idea for torch

as a high school science fair project.

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After watching wildfires devastate

communities near his home in the Bay area.

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His prototype won awards

at international science fairs,

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and one of the judges, Michael Buchwald,

co-founder of Leap Motion,

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was so impressed that he helped

to turn the project into a real company.

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Since then, Vasya has gone from student

innovator to startup CEO,

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building a company that's now deploying

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wildfire sensors in high risk zones

across California and beyond.

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Torch sensors are solar powered

multi-sensor and devices that detect heat,

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smoke and gas in real

time, covering ten acres

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per unit and sending alerts at the moment

a fire starts.

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It's like smoke detectors

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for the outdoors,

but smarter, scalable and connected.

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Via LoRaWAN

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after the devastating LA fires

in January of: 2025

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which destroyed over 18,000 structures

and caused upwards of $250 billion

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in losses, Vasya and his team

rushed into the burn zone to install torch

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prototypes in neighborhoods

like Encino and Griffith Park.

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Now they're scaling up with plans

for thousands of sensors

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deployed this year, including partnerships

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with cities, utilities and communities

trying to get ahead of the next fire.

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To understand

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where LoRaWAN meets real world impact,

you've got to talk to people like Vasya.

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Here's our conversation.

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Vasily, thanks for coming on today.

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Of course. Yeah.

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Thank you. Appreciate appreciate

having me. I'm psyched to have you.

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We got the LA. Fire is top of mind here.

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It's the end of March 2025.

Those were two months ago.

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And that's where torch

kind of sprung to the the public.

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Walk me through,

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like how you guys deployed for that?

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Did you know that stuff was coming?

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Were you deploying as they went down?

Like what?

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What happened?

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Oh, yeah.

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So definitely very unexpected event

as it is for LA

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or the wrestling that two states

or the rest of the world.

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I think the biggest learning

we have from that all of us have

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is that, you know, wildfire is our

not just a seasonal problem.

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It can happen year round

and it can happen anywhere.

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So for us, you know, as a start up,

the story goes that,

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during that time,

we were actually preparing for a S&P

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500 utility deployment of several

hundred sensors on the East Coast.

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And so we're basically

we're doing some last testing

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and some last checks

about the connectivity.

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And then, you know, January 9th happened

and we saw the news

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and the Palisades fires

basically burning through all of LA.

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And so that's when we realized, like,

you know, oh my God, like, this is

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this is happening, this is historic.

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And it's such a tragic situation.

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And at the same time,

our technology is literally built

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to prevent this and to stop things

like this from happening.

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As a early stage

outdoor fire detection sensor.

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And so we basically

just sprung into action.

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My CEO was actually in England

on a family trip, and he flew out

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the next day was in, in San Francisco

the the same afternoon.

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Just because,

you know, the time difference helps

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in this case a little bit.

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And we talked about, you know, 25 sensors,

how much we could fit in the car

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and just drove down with Starlink units.

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Sensors like the whole doomsday kit, the,

you know, gas mask, etc..

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And basically,

you know, we didn't really have any,

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any access to red tape

or any connections going into this.

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We just knew that our technology

is something that can help,

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and our technology is something

that can not only prevent this

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from happening in the future,

but also in the current situation,

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can help to detect

ember fires, re ignitions, Re sparks, etc.

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and so we just come up to areas

that were close to the fires,

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like kind of yellow evacuation zones,

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and we just started talking

to everyone on the ground

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and giving them sensors

and giving them access to our platform

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that had, all the data

for fires in real time.

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So it wasn't just like the satellite data,

but it was also data from our sensors

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that we were just putting out,

you know, in different locations.

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And so slowly, you know, actually

little very quickly this snowballed,

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into, you know, big deployments

like in, in different areas.

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So we were putting them in

Encino and, and, woodland Hills

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and like Hollywood

near the Sunset Fire, etc..

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On the second day, within 24 hours,

we were escorted by the chief Ranger of LA

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parks to the top of Griffith Observatory

and putting sensors there.

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And then basically,

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you know, just getting more

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and more plugged in with the scene

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and with the whole kind of emergency

response crew there.

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So slowly, you know,

we were able to basically help them

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to get real time on the ground data

to as many people as we could,

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which was our mission from the start.

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So we, you know, given this B2B focus

that we had in the B2B deployments

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that are still going on,

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we still were able to help just normal

people with data as much as we could.

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Got it.

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Okay, so the torch sensors

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are just a they're a sensor

that has a little bit of AI in them.

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They're living on the edge.

They're connected via LoRaWAN.

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So they're basically saying,

hey, I see this fire. It's over here.

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You guys should know about it.

And they transmit that back over.

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Helium is LoRaWAN network.

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Is that the

the kind of encapsulated story there?

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Correct. Yeah.

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So these are solar powered sensors.

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They are they're unique in the sense

that they combine

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a lot of different sensing modalities

that we never combine before.

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So we have infrared camera,

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optical camera, spectral analysis,

gas sensing, temperature, humidity.

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All these things happen at the same time.

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And one solar powered sensor that works

indefinitely with no recharging.

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And yeah, we're able to

because we were able to utilize the helium

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network specifically in LA especially,

there's such a wide amazing coverage

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and they were able to reach basically

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any part of the city immediately,

just with one click of a button.

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They just online connect

and it will monitor any ignitions,

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near the sensor, you know, indefinitely.

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And so we were able to detect fires

within three minutes of ignition.

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And, you know, anything

within with good line of sight,

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up to ten acres for one sensor

with worst line of sight.

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You know, we have to rely a little bit

more on the gas sensing,

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but that's why we combine

all of them together.

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We combine

all of these different variables,

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even if each one of them by itself

is not that strong.

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The combination is what creates the most

accurate fire detection in the world.

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It's right and you've been doing this

since high school.

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I saw that in early high school.

You figured out a fire detection sensor.

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So this this isn't something that you just

kind of thought of yesterday.

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Exactly. Yeah.

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So the story goes that basically I'm, I'm,

I'm from a family of scientists.

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Both of my parents are PhD scientists.

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So growing up,

I wasn't really going to parties.

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I just to the science fair projects

with my dad, since middle school.

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And so we would always develop

every single year,

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like a device that could solve

some kind of real world problem,

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whether it was for the California drought.

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We made the sensor that I could

basically project in 3D, like,

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moisture around plants

so you can see water,

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or it was a device

to detect skin cancer, etc..

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And so the, the

my my senior year of high school,

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it was 2017,

we had the crazy Napa Valley wildfires.

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And I'm from near San Francisco,

eastern, eastern, San Francisco Bay area.

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So we had, you know,

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these crazy smoke clouds and obviously

kind of seen the devastation firsthand.

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Always driving by these, these crazy fires

on the way to Tahoe, etc..

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And so, yeah, basically that's that's

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how I had the idea that, you know,

why is this never detected early enough?

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Why is it always allowed

to get out of hand?

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And it's still is, as we see every single

time allows to get out of hand.

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So yeah, we did a science fair project

with my father who

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a you know, he's a, UC Berkeley

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PhD researcher, or as he used to be after

that was founded, our company together.

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And that project won,

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the first place

at the Intel International Science Fair.

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And then after, when I was already

in college, University of Pennsylvania,

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I got connected with a couple investors

in San Francisco

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who were just very interested in the idea.

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So that's how we found that the company.

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Yeah, yeah, yeah.

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You're like a super nerd.

You got an asteroid named after you.

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It's like I got every single nerd credit

that's out there.

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And then a degree in, what is it? Computer

science and economics.

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So the economics side,

let's maybe talk about that is

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what does the business

model look like here.

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Do you go to

I mean I can imagine this being

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you go to a city and you're like,

hey, I can tell,

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I can tell you guys before

you'll know when a fire is starting.

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And this is what the subscription

costs or how does that work.

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Yeah.

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So definitely the the best use case

for torch is protecting high value assets,

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whether it's a city or a large business

or utility or there's a lot of different

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use cases, but

it's this kind of hyperlocal detection.

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You know,

there is obviously other solutions out

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there, such as satellites

or large centralized camera solutions

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that are very expensive

and protecting vast areas of land.

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And all of those things,

they don't detect fires as early as we do.

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And, you know,

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and that's why we're focused on this

more high value asset, local detection.

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Right. And local data.

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So, the way it works from a business

perspective, yeah, we basically, you know,

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have a both a Asus aspect to it

in terms of the subscription

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and also, kind of hardware costs

to cover the hardware as well.

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The exact, breakdowns

of that depends on this.

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It's kind of like a seesaw situation,

right?

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It depends

on the preferences of the customer.

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Some some budget, some,

you know, just kickback situations require

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like capital to be more loaded

upfront for certain sure contracts.

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Some people prefer

the more of the subscription model.

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But obviously there's a lot of monitoring

that goes into this.

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We combine a lot of the data,

both from our local sensors on the ground,

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as well as all the

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third party fire information, air quality

information, weather information, etc.

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win information.

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So I if you combine those two things

together, you create the most accurate

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fire monitoring

because you now have both the local data

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physically coming from real time sensors,

as well as all the data

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that's available to something

like watch duty or weather apps.

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Right.

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And so that's that's something

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that has not been done before

and does not exist right now.

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And so that's how you

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have these super accurate models of where

the fire is going to go next of like how

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how you can spread where can be put out,

where's the highest risk, etc..

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So there's a huge,

you know, data element to this as well.

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Yeah.

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Super cool.

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So you're basically deploying a

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a weather station as well

because you're tracking all of that.

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Is that wind speed and direction

I'm assuming or now.

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So we yeah, we have

we use third party for wind speed.

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We have temperature, humidity,

relative humidity, etc.

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on our sensors.

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Okay.

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I'm just saying that the other

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the reason that wind speed and wind

direction, etcetera matters.

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And there's other sources for that.

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But the reason that it matters is because

you would know where smoke came from.

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For example,

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if you know where smoke came from

based on both die and on the ground data,

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then you kind of know,

like where it's going to go next, right?

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So there's a lot of again, combining

both is super, super important here.

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Yeah.

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One of the funny things about LoRaWAN

and for those of us

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who do it is

it's like a super nerdy fun thing to do.

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And you're like, oh,

I'm gonna get this codec.

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And this uplink just came through.

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But it turns out

when you're selling this stuff,

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no one really cares

about hearing about it.

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When you're talking to a customer,

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do you ever mention LoRaWAN

or only if they ask about it?

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Yeah. No. No one. Really?

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I think in general, customers, care more

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about the value that we bring to them

and how much money we can save them.

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How much?

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How much,

I guess, like emotional, relationship

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they have with their assets

and their their their belongings.

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And it can, you know, burn up in a fire.

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Sure. Specifically LoRaWAN. Yeah.

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I think it's something that allows us

to create this, like one click solution.

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I just press a button and it works.

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And like seeing that is much more powerful

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than saying specific details

about how we're going to do that

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when they ask, of course.

So we describe it as well.

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Yeah.

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Right on.

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And do these things

also have cell backhaul as well.

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Or it's they're just running off LoRaWAN

just is there a an option for you,

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depending on what coverage

is like to use different radio protocols.

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So right now we have right now,

in the current version of the sensors,

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we are using only LoRaWAN.

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We have a, a couple different

developments in terms of IoT solutions

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that I don't want to talk about right now,

but they're coming out really soon.

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That will also basically be other options,

not just LoRaWAN.

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Super, super cool. That's right.

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I mean,

I always like to hear about LoRaWAN,

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but it's good to have backups,

you know, when you need them.

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Okay.

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So when you're

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going coming back to the business side,

when you're coming into a customer,

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if it was me, I'd be looking at whatever

going into a new city to,

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I don't know, in Oklahoma or Tuscaloosa

or Chicago or whatever and say,

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hey guys, looks like you guys

might have a problem with fire detection.

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Here's how much I think, here's

how fast I think we can detect it.

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And here's

what I think the savings will be.

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Or is the pitch something

a little bit different.

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So it depends.

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It depends obviously significantly

on who we're talking to.

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I think if we're talking to big,

utilities and businesses,

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the biggest pitch is that, you know,

we are we are saving this amount of money,

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especially not just in terms of damages

that happened once a fire is there,

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but also just in the sense

of like labor costs of monetary.

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Right?

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There's a lot of labor costs for monetary

and a lot of labor costs for coming

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and checking on different things.

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If you have remote plug and play sensors

that work,

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indefinitely for solar power,

that saves you cost significantly, right?

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So we focus more on that

when we're talking to cities on landmarks.

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It's a little bit more focused on,

you know, protecting the city's history

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and like the cultural aspects

and a little bit

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more of an emotional pitch

towards that area.

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I just, you know, that kind of topic,

I guess

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the money aspect also matters a lot.

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But this a little bit of a different pitch

there. Yeah.

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Oh, interesting. Okay.

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So just depending on the customer

you're tailoring I mean that makes sense.

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You're telling the pitch them

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and making sure that you're serving

the need that they have.

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Of course. Exactly.

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I always, I was pitching to the people and

and what connects them directly.

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Right. Got it.

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And then it sounds pretty cool

in that for folks

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watching this who are wanting to deploy it

towards sensor.

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Is that something I think you and I had

first talked when I was I mean, I'm

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down in San Diego

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and it was going on in LA

and I saw this thing like, hey, you know,

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I want to put torch torch sensors

anywhere.

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Is this something that you're going

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to roll out for homeowners,

or is it just going to be street

313

: 00:13:49

kind of B2B beta G which B government

is going to be any kind of B2C aspect?

314

: 00:13:54

Should I be thinking

about protecting my neighborhood?

315

: 00:13:56

Yeah.

316

: 00:13:57

So currently we are focused

more on B2B deployments because, you know,

317

: 00:14:00

that's been going well.

318

: 00:14:01

And we have these, you know, multi hundred

319

: 00:14:03

sensor deployments that are going towards

protecting big assets.

320

: 00:14:06

Of course, even you know, me

personally as a founder,

321

: 00:14:09

I love the whole consumer angle

322

: 00:14:10

and of course very interesting

and fun to build up business.

323

: 00:14:12

And so we definitely have that in the plan

324

: 00:14:14

right now,

just operationally towards deployments.

325

: 00:14:17

We want to focus on continuing to prove

our technology with bigger customers,

326

: 00:14:20

taking their feedback

and really proving it through

327

: 00:14:23

use cases of fires happening,

how much money was saved, how many assets?

328

: 00:14:26

We protected different locations around

the United States, different stakeholders.

329

: 00:14:30

And when you prove it through that,

then it's easier

330

: 00:14:32

to get into the insurance business

and the other partnerships.

331

: 00:14:35

I can really quickly you know, basically

snowball the whole consumer angle as well,

332

: 00:14:39

because as soon as you have

333

: 00:14:40

an insurance partnership,

they can have lower premiums, etc.

334

: 00:14:43

it's really easy to spread

335

: 00:14:45

the safety net across entire communities

and protect them.

336

: 00:14:48

That said, you know, even though

337

: 00:14:49

we're not focusing on that as as heavily

right now,

338

: 00:14:52

we're still doing

we just dropped this La beta program

339

: 00:14:56

where we are, focusing on La residents

and just giving them, 50,

340

: 00:15:00

you know, limited amount of 50

torch sensors.

341

: 00:15:02

So we want to get, feedback

and learn from consumers as well,

342

: 00:15:05

even though we're not directly

selling to them right now.

343

: 00:15:07

We want to be able to give it

to a limited,

344

: 00:15:09

you know, set of people

who are very interested

345

: 00:15:11

and just passionate about the technology

and the subject and learn from them

346

: 00:15:15

and what their desires

and what their needs are,

347

: 00:15:16

and then create a solution for consumers

that is very tailored towards their needs,

348

: 00:15:21

very tailored towards

their wants and their, I guess, use case.

349

: 00:15:25

Yeah, yeah, yeah.

350

: 00:15:27

I mean, I want, I want to know

when my neighborhood catches on fire.

351

: 00:15:30

So as soon as those things are live

on the website for me to buy, let me know.

352

: 00:15:35

Is there anything else that

353

: 00:15:35

people should know before we sign off

about, about torch sensors?

354

: 00:15:39

Yeah,

I think, you know, we have a, again, like

355

: 00:15:42

I said, a lot of inbound interest

from a lot of different businesses, etc.

356

: 00:15:46

and of course,

357

: 00:15:47

especially homeowners and communities,

especially after the LA fires.

358

: 00:15:50

We're still looking to partner

with a few more,

359

: 00:15:52

you know, big B2B partners right

now, especially with governments or with,

360

: 00:15:56

businesses

that want to protect their assets.

361

: 00:15:59

We have,

362

: 00:16:00

you know, about, I would say, hunt 102

hundred sensors left for the spring.

363

: 00:16:04

And, yeah, we would love any,

you know, interest,

364

: 00:16:07

any more interest from partners

that want to the wants

365

: 00:16:10

to test out our technology

or want a demonstration of how it works

366

: 00:16:14

or just want to see, you know, a fire

being detected on their property.

367

: 00:16:18

Always,

always ready for those partnerships.

368

: 00:16:20

Yeah.

369

: 00:16:20

That's right, because you've done a bunch

of, detection with prescribed burns.

370

: 00:16:23

So it's pretty easy to say,

hey, there's there's no fire.

371

: 00:16:25

Watch this.

Now there's there's a fire. Exactly.

372

: 00:16:27

Yeah. We can also

we also do a lot of demos.

373

: 00:16:29

So, you know, go to a parking lot

or a certain

374

: 00:16:32

area of the customers

that are okay with burning a small flame,

375

: 00:16:35

and we'll put sensors around it

at different distances

376

: 00:16:38

and in different scenarios

in different kind of locations,

377

: 00:16:40

and then light up a flame it with show

detecting and everyone getting call

378

: 00:16:44

and a text message, an alert.

379

: 00:16:45

And it's like, oh,

it's like a magic trick, right?

380

: 00:16:47

Everyone's oh my, yeah, it works.

381

: 00:16:48

And it's always very, very effective.

382

: 00:16:50

And and fun to do for me as well.

383

: 00:16:52

Yeah, yeah.

384

: 00:16:53

Well, I'd be remiss

if I didn't ask this then.

385

: 00:16:55

How far? Like,

what are the parameters for detection?

386

: 00:16:57

Can you see something a mile away?

387

: 00:16:59

Ten miles away, 200ft away.

What does it look like?

388

: 00:17:01

Yeah. So, like I said,

we focus on this hyperlocal approach.

389

: 00:17:04

So one sensor covers up to ten acres.

Ten acres.

390

: 00:17:07

So a ten acre circle is a circle

with a radius of 113m.

391

: 00:17:12

That is our kind of bread and butter.

We do.

392

: 00:17:14

We can detect something

393

: 00:17:15

farther away if it's a very large flame,

if it becomes something big.

394

: 00:17:19

But we want to focus on things

that are basically the size of a campfire,

395

: 00:17:22

or the size of a car,

and the size of a car within three meters

396

: 00:17:25

within three meters from up to ten acres

is kind of our main claim.

397

: 00:17:28

Yeah. Oh, interesting.

398

: 00:17:30

Okay,

so in order to do much bigger deployments,

399

: 00:17:33

you either have to change the sensors

400

: 00:17:34

or just have a really dense

sensor deployment.

401

: 00:17:36

Yeah. Yeah.

402

: 00:17:37

So if you want, you know, let's say

cover a forest, that's very dense.

403

: 00:17:41

We would rely more on gas sensors.

404

: 00:17:43

But also like I said before,

that is not the primary use case here.

405

: 00:17:46

Right.

406

: 00:17:46

Because we want to protect the high

value assets that hold a lot of value

407

: 00:17:50

to their owners.

408

: 00:17:51

And they need this local,

409

: 00:17:52

very i.q protection at the stage

of a small campfire within three minutes.

410

: 00:17:56

Boom. Know about it, put it out.

411

: 00:17:58

Yeah, yeah, that's it's way easier

to put out a campfire than an entire city

412

: 00:18:02

that's burning.

413

: 00:18:02

Okay. Yeah.

414

: 00:18:03

We'd like to use this,

phrase that, you know, in, in the kitchen,

415

: 00:18:06

the the chef puts out a fire on the stove.

416

: 00:18:08

They don't call up the firefighters.

417

: 00:18:10

So same, same concept here.

418

: 00:18:11

So, you know, about early enough. It's

very easy to stop it.

419

: 00:18:13

You don't need to even involve anyone.

So love it.

420

: 00:18:16

Dude, thanks so much for coming on.

421

: 00:18:17

I know you're super busy as a founder,

422

: 00:18:19

so I appreciate you taking the time

to share torch sensors with us today.

423

: 00:18:22

Totally. Yep.

Thank you so much. Appreciate it. Time.

424

: 00:18:25

That's it for the business of law win.

425

: 00:18:27

Thanks for listening.

426

: 00:18:28

If you enjoy the show

and want to learn more,

427

: 00:18:30

the podcast home on the web is meat

sideshow.

428

: 00:18:34

That's MT Sky dot show.

429

: 00:18:38

There you'll find calculators to estimate

the impact of IoT usage on your business.

430

: 00:18:42

Be able to make guest suggestions.

431

: 00:18:43

If you know someone who you think

432

: 00:18:44

should come on the show

and easily get in touch with me.

433

: 00:18:47

If you think the show is useful

for LoRaWAN, please leave a review

434

: 00:18:50

wherever you listen to this.

435

: 00:18:51

Ratings

interviews really help podcast grow.

436

: 00:18:54

Finally, an enormous

thanks to our sponsor, the IoT

437

: 00:18:57

working Group at the Helium Foundation,

for supporting this show.

438

: 00:19:00

If you want to try one out for yourself

without asking anyone permission,

439

: 00:19:04

you can sign up for a Meteoscientific

account at console.meteoscientific.com

440

: 00:19:09

and get your first 400 data credits

for free.

441

: 00:19:12

That's enough to run a sensor for

about a year if you're sensing once a day.

442

: 00:19:15

Right on. See you on the next show.