Britt Antley, Industrial IoT specialist at WIKA and former Chevron operator, talks about what actually drives adoption of IIoT in the real world—and why the shift from control systems to monitoring is one of the most important changes happening in industrial environments today.

With nearly two decades at Chevron, Britt brings a grounded perspective on how large-scale operations think about technology. He explains how his work evolved from traditional IT and process control into industrial IoT, and why LoRaWAN-style deployments fundamentally change the equation. Instead of months-long installs and expensive hardwired sensors, companies can now deploy low-cost devices in minutes, dramatically lowering the barrier to entry for instrumentation.

The conversation explores how IIoT creates value beyond simple cost savings, especially in brownfield environments where the goal is to “put eyes” on systems that were previously manual. From monitoring tank levels to reducing unnecessary operator rounds, Britt breaks down how better visibility leads to improved efficiency, safety, and decision-making.

Britt also shares how he approaches new customer environments—starting with understanding operations, identifying manual processes, and uncovering high-impact opportunities for instrumentation. The discussion highlights a key insight: many systems don’t need high-frequency control, just reliable, periodic data.

The episode closes with a deep dive into WIKA’s Sentinel sensor, including how combining vibration and ultrasound enables earlier detection of equipment failures and extends predictive maintenance timelines from weeks to months.

Britt on LinkedIn

WIKA

Today's guest on

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MeteoScientific's

The Business of LoRaWAN is Britt Antley,

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an industrial IoT practitioner

who spent nearly two decades at Chevron

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and now helps companies deploy real world

IoT solutions at Wika.

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His perspective matters

because it comes from field

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working inside large scale operations,

then translating that experience

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in a practical deployments for companies

that are just getting started.

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In this episode,

we walk through his path from traditional

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IT and process control into industrial IoT

and what actually changes

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when you move from controlling systems

to simply observing them.

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We get into the economics

and speed of LoRaWAN style deployments,

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where a $10,000 hard wired sensor becomes

a $500 device you can install in minutes,

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and how that shift enables entirely

new use cases.

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We also dig into how companies

uncover opportunities for IoT,

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especially in brownfield environments,

and what it really means

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to put eyes on systems

that were previously manual.

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We finish up by covering workers

sentinel sensor, including how adding

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ultrasound extends predictive maintenance

from weeks out to potentially months out.

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This episode is sponsored

by the Helium Foundation

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and is dedicated

to spreading knowledge about LoRaWAN.

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If you'd like to try helium

publicly available global LoRaWAN for free

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and support this show, sign up at Meat

Sideshow Slash console.

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Now let's dig into the

conversation with Brittany.

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Brett,

thanks so much for coming on the show.

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Super psyched to have here. Awesome.

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Nick, thanks for having me.

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Excited to talk to you about LoRaWAN.

Yeah.

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I'm psyched.

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So you were at Chevron for geez,

almost 20 years, 17, 17.

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Okay, three short of two decades.

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Would you walk me through

kind of how long you've been in IoT?

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Was that IIoT industrial IoT?

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Was that there the entire time,

or was that something fairly recent?

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Kind of. Why did you get into it?

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So Chevron I kind of bounced around

within the general IoT space.

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My first experience kind of on the

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OT operational technology side,

I was in IT audit.

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So while I was in audit

I worked on auditing PCN systems.

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From there,

I moved into a role as a PCN administrator

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at a chemical plant

outside of New Orleans.

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I was there for four years,

got more familiar with kind of the OT

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side of things, and then I guess in 21

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I moved over to the industrial IoT space.

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Chevron big company.

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Obviously they have a pretty big team

dedicated to working on your IoT.

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So while I was there,

I got to kind of touch every aspect

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of industrial IoT

within a large multinational.

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Obviously, your oil and gas company.

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Yeah.

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Was there anything that

when you got over there

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that was a surprise to you

or that you felt like,

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oh, this is something super cool

that like, I wish more people knew about?

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I would say one of the

one of the big kind of eye

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opening things for me was there's

kind of this difference between

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your traditional operation technology,

your process control systems.

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You got your hard wired,

everything is very tightly controlled.

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Then moving into the IoT space,

first of all, at Chevron

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and kind of in general on the industry,

you don't see much control in IoT.

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It's more just monitoring.

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So for me,

it was kind of a mindset change moving

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from the process control side over to IoT.

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Well, at the same time, IoT

allows you to be so flexible,

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so agile compared

to your traditional process control.

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You're able to much more quickly, easily

and cheaply

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deploy these IoT solutions.

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For me,

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that was a huge eye opener compared

to the more traditional side of things.

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Oh, interesting.

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Just because they are pretty easy

to deploy and especially with LoRaWAN.

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Although across all of the IoT

technologies,

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you're just putting a thing in there,

kind of slapping it on and walking away

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versus figuring out how to control stuff

and make sure you don't screw it up.

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Absolutely.

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Like deploying a traditional sensor

in a control system, obviously you're

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you're running power out there,

you're running Ethernet out there.

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You have to go through

this huge management of change process,

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which takes months.

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All this equipment is very expensive.

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One sensor, it can be $10,000.

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Now you go to like a lower win

IoT situation.

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That sensor is going to cost 500 to $1000.

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And assuming

you already have your network in place,

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literally,

you walk up to a piece of equipment,

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you slap that sensor on there and within

a couple of minutes you've got data.

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So just the ease and quickness

and the cheapness with

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which you can deploy

IoT is really a game changer in my mind.

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Was there a sense in Chevron

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that IoT kind of wasn't

something they should do?

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It seems like one of the things

the biggest retardants to IoT

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adoption is people are just like,

I don't know about that stuff.

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I don't know if we really need it.

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And it seems like it's super valuable,

but it's like making the case

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that it's useful, as is probably

just as difficult as figuring out,

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if not more, is figuring out the RF

and the rest of the,

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you know, frequency hopping stuff.

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Yeah, while I would say there was,

you definitely ran to some resistance

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in deploying IoT solutions

at the end of the day,

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Chevron and I would say oil and gas

in general, they're pretty early adopters

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into the IoT LoRaWAN space,

especially within the US market.

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I know you do.

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You know the European markets a little bit

ahead of us, but in the US market.

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Oil and gas

was pretty early on the adoption phase.

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So the fact that Chevron had built out

this huge

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team,

you put this huge investment into it.

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With that,

they were able to kind of create their own

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ecosystem in very quickly.

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You start to realize value out of IoT.

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And that's something that they were quick

on a lot of other companies are very kind

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of just starting to dip their toes

in, starting to figure out what is IoT.

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Honestly, that's

what I'm doing it like to figure out

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these smaller to medium sized companies

who may not necessarily know IoT.

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Irwin.

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What these technologies are,

I'm trying to I'm here

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to help them figure out

how they can create value out of that.

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Okay.

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That leads really nicely

into the next question, which is, is there

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anything beyond just saving money

that you use when you're talking to small

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and medium sized companies as a reason

for them to adopt industrial IoT?

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Yeah, absolutely.

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I think the biggest thing

adopting industrial IoT

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is giving you eyes

where you currently don't have eyes.

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So a lot of the adoptions we're seeing are

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mostly

in the kind of the brownfield space,

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these established facilities

or plants, whatever it might be.

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So it's already there.

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And it's saying

with your current infrastructure,

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your current layout,

how can you get more value out of this?

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How can you get more efficiencies?

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How can you put eyes on something

that currently doesn't have eyes?

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Currently,

an operator has to go walk around

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to 60 tanks a day and visually

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look at something

visually take a level on a team.

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How can you make better use of their time?

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Instead of walking those rounds every day,

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they can look at a screen that's

going to give them the same information.

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They can get alerts that are going

to give them the same information.

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So it's kind of more of a proactive

approach.

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Right.

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And I bet that makes sense

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to a lot of a lot of business owners

who are saying, hey, I'm paying for this

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like expensive engineer.

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I can use their time to help design stuff

and create new things, rather than have

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to walk around and

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look at a button.

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Is there a bunch of conversion

of analog devices into smart sensors

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with what you're doing?

Or is it more like,

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hey, let's put something new on here,

walk me through that.

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So what we're mostly seeing now is

let's put something new on here.

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We have some type of equipment

that's currently not instrumented.

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So how can we get some data out of that?

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Essentially I do see slowly

and probably more so in the future.

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Going forward,

there will be more replacing

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those kind of hard wired with IoT devices.

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So I know, in the process control

industry, a lot of the life cycles on

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these systems are ten, 20,

maybe even 30 years.

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As they start to age, they're looking

to upgrade them, replace them.

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Well, you can replace a system

some five, $10,000 sensors.

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You can go

the same route, do the same thing, or for

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ten, maybe 20% of the cost,

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you can make those IoT as long as you're

not controlling anything.

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If you're just looking to monitor

it, have eyes on it.

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IoT is a perfect solution

in that situation.

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Interesting that there's such a point of

differentiation with this control piece.

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I haven't heard

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folks talk about that as much,

and that sounds like that's

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just coming from the background.

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Like, hey, I used to control everything,

and now I'm seeing that there's value

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in a lot of just observing

what's going on.

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Yeah, absolutely.

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And a lot of current process

control systems.

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Yeah. Everything is hard wired.

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It's super industrial, super heavy duty.

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I mean, you're getting millisecond

readings.

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Yeah. And that's good for some situations.

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But a lot of times

if you get a reading every 20,

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30 minutes,

even every hour, that's perfect.

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I mean, how often is a tank

changing level?

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They're doing draws

maybe once or twice a day.

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Well, you don't need readings

every second on that.

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You put a $500 thousand dollars

sensor on there.

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You take readings every 30 minute,

every hour.

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You're getting the same quality of data

for a way cheaper.

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Yep, that makes a ton of sense

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when you're coming into a new organization

and a potential customer.

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What are the ways that you think

about uncovering or discovering

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opportunities for them to use IoT?

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I think a big part of that

is just understanding their operation,

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understanding their business,

understanding their value

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chain, understanding their key processes.

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And as you start to look at those,

you can see,

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hey, you've got this process here

that's hugely automated

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and you got a lot of people involved there

manually touching things,

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manually looking at things.

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Not only is at a time

where it can also be a big safety issue,

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especially in the oil

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and gas space, they're huge on safety,

so that's always a big concern.

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But yeah, looking at those kind of

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what are their important systems,

what is currently manual,

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what could we easily go in and instrument

and get them data,

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get them actionable insights

and let them really have

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a great vision of this system

where essentially turning manual processes

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into more automated processes

now makes sense.

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So you go and understand the system

and then sit and kind of look

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for these key points of like, hey,

we're obviously where can we save money?

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Where can we make you more efficient,

where can we make you more safe?

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And maybe there's like 2 or 3

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more kind of columns that you,

that you hit or pillars that you hit.

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But that sounds about right.

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Yeah. Cool.

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So walk me through this sentinel thing

that we CA or Waka has just brought in.

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What is this thing?

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Yeah.

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So Sentinel,

it's lead by a company called a system.

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A system is a company that Wyck

recently became the majority owner of.

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So the Sentinel is a sensor.

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The most traditional way to think about it

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is it is a machinery health

monitoring sensor.

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So within this one sensor

there is temperature.

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It is also measuring the vibration

tri axial vibration.

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And I think the real secret sauce within

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it is

we also have ultrasound measurements.

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So the vibrations pretty typical.

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We see that a lot of different companies

have their version of vibration sensors.

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But bringing that extra level

of ultrasound into the sentinel sensor,

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what that allows us to do is get a whole

nother level of analysis.

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So your traditional vibration sensor,

you can go to

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five,

maybe ten kilohertz, a vibration detection

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with the ultrasound, you're able

to take that up to 60 to 70kHz.

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Now what this ultimately allows you to do

is to get a further look into the future.

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So you put this sensor on

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any type of rotating machinery,

whether that's a pump, a motor,

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a compressor, you put it on there

and it's able to perform analysis.

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A big part of this sentinel

is also a machine learning aspect

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that we're able to do on our platform.

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So yeah, you take in all this data,

you kind of determine what's baseline.

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And then off of that you're able to say,

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hey, I'm detecting some weird sound

and the machine learning

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is able to actually say, hey,

I detected this type of sound.

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This can mean

that you have a bearing going bad.

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And once you have that level of analysis,

then you can have one of your engineers

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go and say, hey,

something's going wrong with this motor.

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Let me go out and check it.

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Whereas your traditional

kind of processes,

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maybe once every week, every month

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at best, you have a mobile sensor

that you put on a piece of equipment.

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You kind of listen,

I mean, even more traditional,

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you have engineers out there

who will literally tap on something,

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or they'll put their ears up to it

and listen.

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And these are

professionals are very good at their job.

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But when you can put a sensor on there

that's doing that 24 over seven

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and is able to do it at, a deeper level,

I think that's a real game changer.

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What's the performance difference

when you add

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an ultrasound versus

just the vibration sensors?

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There's a

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maybe not a metric ton of those

in the market, but there's a lot of

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a lot of kind of machinery

listening sensors on the market.

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There's ultrasound

sounds like it's pretty fancy and special.

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Like how much better is it?

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I guess the question. Yeah.

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So the best way I know to quantify that

from data I've seen is that, vibration.

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And typically they can see issues

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that are maybe a couple weeks

or a month out.

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So we're starting to tuck this vibration.

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Something's going on.

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Maybe in a couple weeks

it could become a real issue.

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So I had to do something about it

with the ultrasound capability.

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From what I've seen,

were able to detect issues

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that are like three,

maybe even four months out year.

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Okay.

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So it's less severe

that what the vibrations able to detect.

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So you have this little thing

that's starting to go wrong.

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Not an issue now but keep an eye on it.

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Maybe go ahead and order that back up part

so you can have it ready.

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Yeah. So that's that's kind of the beauty.

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It allows you to see kind of

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further into the future

to do your predictive maintenance.

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Oh that's that's rad.

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Super cool.

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Let's see.

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Let's wrap this up a little bit.

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On a slightly more personal note,

you're way into beer.

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We were talking a little bit

about building

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breweries and sensing or sunsetting

whatever it is, instrumenting breweries

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before we recorded.

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Maybe we start with this idea

of kind of consumer versus industrial IoT,

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and what the big differences are and walk

you through kind of what that looks like.

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And is there a difference

or is it kind of IoT as IoT?

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Yeah,

there's definitely a difference there.

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I think it's

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kind of important to understand

and there's also different levels to it.

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One example recently I was at one of

my favorite breweries here in Denver.

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I was talking to the owner.

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He was mentioning

they had a temperature sensor

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in their cold box that had been kind of

iffy, wasn't giving them great data.

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I'm like, oh, interesting.

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Well, my company I worked for, white Guy.

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We actually have a solution

that could solve that, but

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they're using kind of a

more consumer grade IoT.

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It was probably like $50 sensor.

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And for the most part, it worked

well for them.

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And also at this cold box, if

the sensor went bad, the cold box was hot.

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They had other ways,

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kind of secondary ways to look at it

and see what the temperature was.

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So your industrial grade IoT,

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it's not going to be as cheap

as your consumer grade,

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but it's going to be much more reliable,

much more durable.

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It's designed to be in more extreme

environments.

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When you say industrial IoT,

you're deploying at various sites,

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chemical plants, manufacturing facilities,

a lot of times

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there are hazardous gases,

so you don't want anything

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that could potentially cause

a spark in an explosion.

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And we don't want things to blow up.

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So yeah.

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Industrial non-optimal

yeah yeah yeah yeah.

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And not looking for that in general. Okay.

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And then

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just as an example of what you might do

if you had to go in today and today is

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I think we're recording on Wednesday,

by the end of the week,

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you had to close a brewery

on a sensor somewhere.

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And what are Denver, what would you target

as a as the kind of pitch?

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Because that seems like an industry

you're pretty familiar with.

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So you wouldn't

have to learn that much about it.

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00:16:53,712 --> 00:16:55,381

What would you kind of walk into

any given brewery and be like,

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I know they're going to need this.

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So, I mean, temperatures as you age one,

you got all types of mass of equipment

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that's cheating product, cooling it down.

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So being able to monitor that

and keep an eye on it is a huge space.

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I will say that most of the modern

brewing equipment

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usually has all this sensing

kind of already built in.

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If you're buying

one of the new state of the art systems.

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All of this is kind of built

in, which is cool to see, but let's say

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tomorrow, cures here nearby in Golden,

they call me up.

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00:17:31,650 --> 00:17:35,521

Hey, we're having some issues

with our instrumentation here.

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00:17:35,521 --> 00:17:36,922

What can you offer?

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00:17:36,922 --> 00:17:37,423

I'm a go.

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00:17:37,423 --> 00:17:40,959

And number one,

what's your temperature look like?

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00:17:40,959 --> 00:17:43,695

Number two, what is pressure look like?

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00:17:43,695 --> 00:17:46,832

You're moving around a lot of liquid,

a lot of volume.

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Sometimes it's pressurized.

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So being able to monitor that,

keep an eye on it is another huge system.

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Super cool.

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And I can see with certainly

with the bigger breweries, with Coors,

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00:17:56,175 --> 00:17:59,311

or even a kind of midsize brewery

that they're going to be willing to pay

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the industrial IoT prices versus like,

hey, I'll just order this thing

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00:18:03,115 --> 00:18:05,284

off the internet,

have it here tomorrow. Absolutely.

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00:18:05,284 --> 00:18:07,753

I mean, it

obviously depends on the type of system.

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00:18:07,753 --> 00:18:09,888

And industrial IoT isn't for everything.

348

00:18:09,888 --> 00:18:13,692

But in these big manufacturing facilities,

which breweries are

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00:18:13,692 --> 00:18:17,096

I mean, they're just

they're manufacturing a delicious product

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00:18:17,096 --> 00:18:19,565

that we like to drink,

but that's all it is.

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00:18:19,565 --> 00:18:20,899

It's a manufacturing facility.

352

00:18:20,899 --> 00:18:22,134

So, yeah, and something like that,

353

00:18:22,134 --> 00:18:25,204

when you have the huge scale industrial

IoT makes sense.

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00:18:25,637 --> 00:18:26,071

Ripping.

355

00:18:26,071 --> 00:18:27,606

Well, thanks so much for making time today

356

00:18:27,606 --> 00:18:29,808

and coming on

and talking to us a little bit about IoT.

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00:18:29,808 --> 00:18:32,811

We want to hit on the lower end stuff,

but I think for this audience,

358

00:18:33,078 --> 00:18:34,713

they've got a pretty good understanding

of how it works.

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00:18:34,713 --> 00:18:35,414

So it's super cool

360

00:18:35,414 --> 00:18:38,517

to see really the perspective

that you bring to the industry.

361

00:18:38,517 --> 00:18:39,918

Thanks. Thanks. Coming on.

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00:18:39,918 --> 00:18:40,519

Awesome.

363

00:18:40,519 --> 00:18:42,788

Great talking to you, Nik,

and thanks for having me on.

364

00:18:45,457 --> 00:18:48,460

That's it for

this episode of The Business of LoRaWAN.

365

00:18:48,660 --> 00:18:51,430

If you want to go deeper

and actually deploy devices,

366

00:18:51,430 --> 00:18:54,533

the MeteoScientific

Console is the fastest way to do that,

367

00:18:54,833 --> 00:18:57,870

and honestly, it's

also the best way to support the show.

368

00:18:58,670 --> 00:19:02,007

When you use the console, you're not just

listening, you're participating

369

00:19:02,007 --> 00:19:05,577

in the same real world LoRaWAN work

we talk about here every week.

370

00:19:06,044 --> 00:19:09,581

You can get started with the free trial

at Medio scientific.com.

371

00:19:10,315 --> 00:19:13,152

Huge thanks to the sponsor of the show,

the Helium Foundation,

372

00:19:13,152 --> 00:19:16,155

for supporting open LoRaWAN

infrastructure worldwide.

373

00:19:16,588 --> 00:19:20,359

Check them out at helium Dot Foundation

and if the show has been

374

00:19:20,359 --> 00:19:23,428

useful, a quick rating or review

on Apple Podcasts or wherever you listen.

375

00:19:23,462 --> 00:19:24,396

This really helps

376

00:19:24,396 --> 00:19:27,399

people find it and helps the show grow

so we can help more people.

377

00:19:27,733 --> 00:19:29,701

I'm Nik Hawks with MeteoScientific.

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00:19:29,701 --> 00:19:30,769

I'll catch you on the next episode.