Episode 2

Dean Marsh - Using LoRaWAN to Fight Cold & Crime in the UK

🔍 Episode Overview

In this episode, we sit down with Dean Marsh, a veteran in the world of LoRaWAN-powered IoT deployments across the UK. From saving lives in rural Welsh housing to uncovering criminal activity through smart sensors, Dean shares how simple, scalable IoT solutions can drive massive impact—not just efficiency. Whether it's reducing costs, slashing CO₂ emissions, or catching drug gangs, this one’s about using LoRaWAN where it truly matters.

🧠 What You’ll Learn

  • How a LoRaWAN sensor helped save an elderly man suffering from hypothermia​
  • Why LoRaWAN is ideal for scaling low-cost, battery-powered sensors in social housing, utilities, and construction​
  • The surprising story of how footfall sensors exposed a drug gang operating out of a residential building​
  • Why changing processes, not just tech, is key to successful IoT adoption​
  • How partnerships (like UK Connect + Daizy) are simplifying enterprise-scale IoT rollouts​

🛠️ Technologies & Use Cases Discussed

  • Social Housing: LoRaWAN for detecting mold risk, fuel poverty, emergency lighting compliance, and smoke alarm automation.
  • Utilities: Millions of LoRaWAN-connected water meters transmitting hourly readings.
  • Construction Sites: Real-time compliance and safety monitoring with LoRaWAN.
  • Optimized Retrofit Projects: Measuring thermal efficiency in homes using multi-sensor data.

đź’ˇ Key Takeaways

  • Start with the pain points: Customers don’t care about the tech; they care about saving time, money, and carbon emissions.
  • Automate compliance: Dean shows how LoRaWAN eliminates manual checks—from emergency lights to Legionella risk assessments.
  • It’s all about process change: Successful IoT projects rewrite outdated workflows—not just add dashboards.

đź”— Resources & Mentions

🙌 Special Thanks

This episode is brought to you by the IoT Working Group at the Helium Foundation.

đź’˛ Support the show!

https://support.metsci.show

Transcript
Speaker:

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 on the business of LoRaWAN.

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We're diving into the world of real world,

high impact IoT with someone

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who's been at the forefront of deploying

smart sensor

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networks in places

that actually need them,

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not just to automate toasters,

but to save lives and disrupt crime.

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My guest today is Dean Marsh, currently

IoT specialist at UK

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connect, a company building

secure connectivity and IoT infrastructure

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across the UK from construction

sites to social housing.

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Dean's career is a fascinating journey

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through the trenches

of public sector innovation.

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He started out in it

at a housing association in rural Wales,

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where he helped

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deploy one of the earliest LoRaWAN

based monitoring systems in the UK

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and in social housing

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that included battery powered sensors

tracking things like humidity

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and temperature to flag issues

like mold or dangerously cold homes.

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From there, he moved to connection,

where he helped roll out

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what's likely the densest LoRaWAN network

in the UK, connecting millions of smart

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utility devices across

cities and rural areas.

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Now UK connect, he's bringing

those same capabilities to construction,

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tackling health, safety and compliance

through scalable, real time IoT.

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In this conversation, Deane shares

how a simple temperature sensor helped

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save an elderly man's life

and how anonymous people counter data

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led to uncovering a pattern of drug gang

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activity stories that remind us

just how powerful these systems

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can be when placed in the right hands,

with the right intent.

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This one is about scale, impact,

and unexpected insight.

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Let's get into it.

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Dean,

thanks so much for coming on the show. Hi.

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Thank you Nik, great to meet you.

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Yeah, I'm psyched to have you on.

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Let's start the journey.

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You've been in LoRaWAN as long as anyone.

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Almost anyone I've met for sure is

I think it was back in:

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You started using it?

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Maybe earlier.

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What was it about it that caught

you and got you really interested?

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Yeah. That's right, almost ten years now.

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So back in 2016, 2017, I was working with

in social housing in the UK.

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I spent most of my career

within the sort of IT sector.

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So at the Housing Association in Wales

we are quite a unique sort of

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problem really.

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So we had roughly 5000 properties

scattered

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all across Wales,

so that there's a lot of traveling there.

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That, that the sort of staff

they found out about problems before

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it was too late. So it's reactive.

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So for example, a property be abandoned

or a leak in there.

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And by the time it was sort of notified

and they found out

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a lot of damage in place.

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And we also used to talk, you know,

what if what if we could get data

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from these assets and turn the

in the reactive into proactive.

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And about that time we were quite lucky.

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We saw LoRaWAN

sort of coming on the scene in Europe.

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And what's all this about?

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We talked about it previously

where we'd have to sort of hardwire

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the properties and put cabling

and that that wouldn't work.

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We couldn't use the tenant

sort of internet.

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So when we saw this new technology

emerge, LoRaWAN.

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So and we just went ahead and bought

a gateway and a load of sensors,

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we didn't have a clue

what we were doing at the time.

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It was it was quite an exciting adventure.

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So, we install the gateway

on to the headquarters in a small town.

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Bit of a learning curve there.

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We hired a cherry picker.

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We did the work ourselves on top.

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Made sure the antenna was good, and then,

that was in place.

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So we start to roll out

these environmental sensors.

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I think there were Alsace errors.

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Temperature, humidity, CO2.

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So we started to roll those out

into the properties, into the homes

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in the area, about 100, 150 at the time.

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And then all of a sudden we start getting

this at this data from the homes there.

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And it was absolutely fascinating.

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We could see

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instantly the homes which were abandoned

and we didn't realize were abandoned,

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fuel poverty, in the UK a lot, you know,

a lot of people are on the breadline.

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They've not got enough money

to heat the homes where there's

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a lot of grants available,

and we could instantly see these homes.

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They've been below sort of,

ten degrees centigrade for a week.

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So with that data,

we start to send the housing officers out.

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And it kind of opened up

this whole new way of working for us.

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And there was so much excitement

going on internally.

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We got shortlisted

for sort of many awards.

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And actually we had a bad winter in the UK

right about that time.

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It was,

I think it was called beast From the East.

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And we saw, one property in particular.

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The at the temperature went below

zero degrees for a week.

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So, yeah,

we sent a housing officer out there

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and the, an elderly gentleman

who was hypothermic at the time.

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So, yeah, we potentially

saved a life there with with the data. So.

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So what LoRaWAN suddenly enabled us to do

was get all this data

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from our houses

really quickly, easily to deploy.

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We didn't need to rely on

SIM cards, the batteries,

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because the nature of LoRaWAN is such low

power, the batteries

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with sort of a half an hour sampling

rate can last up to sort of ten years.

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So it just enabled us to kind of open

this whole new kind of world of work.

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And as a couple of years gone

on, we started to roll out more sensors,

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into homes, getting all this data

and learning from the data as well.

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We made a big,

big kind of impression in the scene.

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I think we were on first

in the UK to actually do that.

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Very exciting.

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And then we started to look at the,

the compliancy side,

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all these sort of manual things

people were doing going out in vans.

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In the UK you had to test emergency

lighting once a month.

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By law.

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You have to do the legionella

risk assessment as well, where you're

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measuring temperature,

the taps and recording

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that we're thinking, right, okay.

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We we kind of got the architecture here.

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Now can we actually automate these things.

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And yeah, we could

so we we set about to begin with

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automating our emergency like testing.

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So we looked at the figures

and we were spending roughly over

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100,000 pounds

a year on emergency lights in alone.

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So we start to target these blocks

where they were coming up

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for renewal of the components,

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and we start to put in these LoRaWAN

enabled emergency lights.

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And that enables us to do the testing

over the air, generate its own report

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in it, literally land in the inbox

every month for the staff to, board.

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And we realized, wow,

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okay,

people are not going out in vans anymore.

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That's a huge CO2 print we just saved.

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And then we we sort of understood, okay,

part of the rent the tenants are paying,

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there's a service charge element

that they're actually paying

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for the emergency

like testing that got removed.

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So it reduced the rent and these blocks,

which was which was absolutely brilliant.

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Not so.

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I started to find an area.

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I'm a big problem solver.

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I love looking at things.

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People are doing the same for years,

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for years and saying like, you know,

can we actually make this better?

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And it kind of took off from me

that I got headhunted for another job.

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Start to do more of the housing side

and take that kind of skill

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set that on a mass deployments in the UK,

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past two years.

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There's a huge momentum

in the UK for LoRaWAN.

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A lot under the radar.

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A lot of the street lighting is LoRaWAN

enabled.

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I'd say almost 90%

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of water meters in the UK at LoRaWAN.

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A lot of support

with the Welsh Government.

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They've rolled out gateways

to all towns and villages.

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So you've got this coverage.

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Absolutely everywhere.

Oh that's fantastic.

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I had no idea

it was so deep across the, across the UK.

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So let's see 2017, you find it,

you kind of work

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through till 2022 at the

what was mid-Wales housing.

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And then changed to another,

another company.

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Yes. It merged with another housing

association called Tight critical.

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At the time it became came pocket and at

that time I'd worked on it all my life.

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You know, I'd kind of gone from, sort

of the days of Novell Network to full.

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I'd seen this in the IoT.

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It just kind of really, I think my mind is

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kind of geared for IoT

and those problems there.

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So I found that area I actually really

enjoyed didn't feel like a job anymore.

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Yeah.

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The past two years

working with the majority of the water

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utility companies in the UK, basically

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deploying massive scale

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LoRaWAN networks, millions of devices.

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And for the water utility companies, it's

basically going from where

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they're getting a handful of rates

every year to hourly rates,

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which made a made

a huge difference, akin to tech

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where leaks

are automatically other anomalies.

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And that was that was very exciting,

very exciting. Now.

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Got it.

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Okay.

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So the the really big savings

from the business side.

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Like I always like

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geeking out on the tech side

just because it's fascinating to me.

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But it's also important for folks

who are watching this to say,

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okay, how would I use LoRaWAN to make

or save money

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is what I'm hearing

you're saying is over and over.

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You were able to find

when you deployed LoRaWAN

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sensors, you almost

you immediately had labor savings.

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And then there was also a piece

that's built on top of that,

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where you start to have a much clearer

picture, much more up to date

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picture of what's actually happening,

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and then can make better business

decisions off of that.

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Is it those are the two main areas

that you're seeing.

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Is kind of business

beneficial for LoRaWAN?

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Yeah.

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The key that the customer doesn't

really care so much about,

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that's sort of the jargon, the buzzwords,

the connectivity.

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You've got to go in there,

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look at their manual processes,

look at find their pain points.

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And I think the main battle I've come

across is actually making the customer

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or potential customer understand

there is a problem to begin with.

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They won't actually realize this

technology exists to automate an area.

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So you want to look at all

their processes.

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LoRaWAN typically

where you've got manual things going on.

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Obviously infrequent sort

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of some once a week or once a month.

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But massive scale,

you know, across many locations there.

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So it's a look at those pain points.

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You've got to

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understand, you've got to speak

the language of ROI to the customer.

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They want to say, right, I'm spending,

you know, X, I'm spending 2 million pounds

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a year with this kit going in, you know,

how quickly is it going to pay for itself?

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And their own wants as well.

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And it's not just

sort of reduction of cost as well.

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You'll see a lot of CO2 reduction as well.

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So in the UK with decarbonization, ESG,

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a lot of a lot of the solutions

will take that box as well.

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So that that that's

a very important to consider.

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But you gotta you've got to understand

them pain points, get them out

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and then work the technology around

that got it.

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So when you're going into a new customer

or talking to a new customer,

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do you have a series of questions that

you ask like, hey, how much is your labor?

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What's your your highest top line expense?

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Are there any things that you're like

over and over?

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When I ask this question, I almost always

find a problem I can solve.

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Yes, exactly.

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Spot on.

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I like to kind of try

and put myself in their shoes.

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I'll go out to site, spend a day with them

and see what they're actually doing.

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And then you start to kind of understand

the picture and another key area as well.

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And I see a lot of IoT projects fail,

but not because of the solution

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and the technology.

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That's absolutely perfect.

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But when you've got a business

and they've been doing

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these processes that have been in place

for 20 or 30 years,

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these manual processes,

they need to be almost completely erased

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and rewritten to deal with this,

proactive approach of data coming in.

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And I've seen a lot of failures in the UK

where they've they've just not

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rewrote the processes

and expected it to work with IoT,

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for example,

with your automated compliancy in housing,

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you want to get it to a point where, okay,

all the testing has been done automatic

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and that it's

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fed into your existing management system

and it updates the component.

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It takes away the admin side there, so it

completely automates the entire process.

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And that's that's

where you get massive wins and adoption.

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Yeah. And let's see connection.

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Recently I think announced a partnership

or preferred partnership with Daisy.

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And so I'm seeing

if I'm getting this right

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that these companies who are providing

the connectivity

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are partnering with companies

who are providing the kind of enterprise

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IoT, maybe visualization

and management side.

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And that's going to be this

trend of like, hey,

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not only should you roll these things out

and get the data in,

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but here's how you manage the data

to make your your business better.

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Are you seeing the same thing

or am I just missing something

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because I'm new to the, to the industry?

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No, that that's absolutely correct.

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So it's so yeah, a UK connects.

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We're thinking okay, long term

with large scale deployments.

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We it's we need to think about.

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Right. Okay.

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Let's take for example

say we're doing a telegraph pole

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monitoring solution

for either electric or fiber.

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And we got 20,000 poles.

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We want to, you know, fixed density okay.

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For one you've got a you've got to build

the project into the application.

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And Daisy is it's brilliant for there.

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So you'd load the project in with your

20,000 poles and the GPS location there.

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Then you'd load your sensors in.

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It's a repository.

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There's a mobile phone app

for doing the install.

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So basically what happens at that point

that you push

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the jobs out to the engineers,

they know exactly where to go.

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They scan the sensor in that location.

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So it takes the human element error out.

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Because if you go to the wrong

notification

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and trying to scan the wrong sensor,

it just doesn't like you.

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So so Daisy is a key key area, a key

kind of component

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in your system to ensure that you're

managing the project correctly.

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You provision the devices.

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You can see they're working okay.

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And what I love about it,

it's got that flexibility

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to integrate easily

into existing applications,

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because you see a lot of the time

with an enterprise customer,

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they don't want you dashboards

or applications.

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They want to use their existing power

BI or whatever's behind the scenes,

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and they just want to parse the data,

so it accepts it and

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process that Daisy makes.

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That makes that really easy to do.

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Got it. And thank you for the correction.

That's UK connect.

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That's not connection that yeah.

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Doctor wood with Daisy okay.

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Super super cool.

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What are like the what are the biggest

problems that you see in in LoRaWAN.

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And kind of

the business of LoRaWAN. Is it.

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You know what are you seeing where

it's like, man, I wish we could solve this

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biggest problems.

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I'd say it's it's usually

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sort of like a culture shift, really?

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Yeah.

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You know, it's more like,

can I explain it?

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Sometimes it's sort of psychology.

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People don't like change.

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Some people don't like change.

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I'd say that's the biggest obstacle.

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The technology works. Works great.

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As long as you for a massive rollout,

you do all your planning,

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make sure that gateways

are installed to spec

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and everything is done right there,

and you'll find this absolutely solid.

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I'd say all night

the actual selling the product,

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it's it's making sure that you can

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speak the language of the customer

and ROI, the technology side.

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Yeah, it just works.

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Got it. Okay.

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So the biggest problem, and this is what

I seem to encounter over and over, is

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just explaining to the customer

what this unlocks for them.

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And it sounds like you've got

a really good, set up downwards, like,

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hey, this will unlock labor savings

and this will unlock new data insights

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that will be important for your

for your business.

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Okay. Yeah.

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Just just falling off what you said, it's

you've got to put yourself in the shoes

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of that customer and understand it

from their point of view.

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And don't go

just take out the jargon completely.

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Yeah.

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Fair enough.

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It's as much as I love talking about

uplinks and the rest of it as soon as I.

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Yeah, if I say any of that, I love that.

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Yeah.

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Let's see that.

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So some nerd stuff

I saw you're into energy harvesting.

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That seems like

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the next big thing in sensors in general,

is just getting rid of the batteries and

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making sure that we're using the energy

that's kind of on site, for that.

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Is there is that true?

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And is there anything else

that you're seeing that you're

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that's coming down the line

that you're really excited about?

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Yeah, that's a great point.

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Actually.

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A massive fan

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of the new sort of second generation

actually helps ancestors come out.

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So, you know, you've got

I think if you roll in I thousands

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of millions of devices, you've got lithium

batteries going into each.

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And if you get around that, with energy

harvesting, it's key.

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For example,

I've used a lot of the, for utility

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hot drop the energy

harvesting CT clamps, for example.

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We've got a large commercial building.

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You can get those in real quick.

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They just kick off, send the data through

and that they're brilliant.

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There's a number of environmental sensors

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as well, which do actually helps the gray

area really, really closely follow.

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Yeah, it's super cool. And do you have any

you mentioned one of them.

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You have any other preferred ones?

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The only one I've seen that have had

my hands is the sis.

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I think it's a ERS CO2 monitor.

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I mean,

I know there's thousands out there,

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I just haven't,

I haven't touched a bunch of.

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Is there anything where you're like,

oh this one is works really well.

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A French

company next lec that they're hard work on

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harder is absolutely,

you know, sort of Cisco.

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Cisco. Great.

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If I can if I can say that it's it's

absolutely solid.

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They have a new, smoke detector,

LoRaWAN base smoke detector

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which meets the UK regulations.

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So for interlink.

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And that's another great area in the UK.

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You have to

for example, as a housing association,

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you sort of go out and manually test

every year if you got that information

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coming over the air from a smoke detector,

it completely transformed it.

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So yeah, check those guys. Okay. Friends.

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:

I mean, I would expect anything in France

to be ahead of the curve.

373

:

That's where the whole thing started.

374

:

So, Good.

375

:

Good to hear

there's no surprise there. Let's see.

376

:

As we wrap this

377

:

thing

up, is there anything that you've seen

378

:

from combining different pieces of data

that's been surprising to you?

379

:

I know that you've done the temperature

and humidity to check for mold growth.

380

:

Is there anything else like.

381

:

Oh, yeah, we did this thing

382

:

and I didn't understand at the beginning

how powerful it would be to

383

:

to kind of stack these two pieces of data

on top of each other,

384

:

but we unlock some new insights

because of it.

385

:

That's a great point, actually.

386

:

An area in the UK,

which is called optimize retrofit.

387

:

So basically you're going end

with a, say, a property,

388

:

what was built in 1930 or 40,

you're putting insulation in there.

389

:

You change the heating you windows,

you improve the efficiency.

390

:

So an area

that so you need to measure how much water

391

:

the property's use

and how much electric gas.

392

:

And then in each room

the the thermal efficiency of

393

:

temperature rising

and then the heat decay there.

394

:

And I think what makes it really easy now

with the sort of the way

395

:

AI machine learning is exploded,

you can basically just,

396

:

you know, dump that data in that

it'll do all the calculations really easy

397

:

if you get out.

398

:

So you've got a,

you get almost like a 3D kind of picture,

399

:

but actually just

just remembered something.

400

:

At the housing association, we,

we put, people characters

401

:

onto the blocks of flats,

just out of curiosity, seeing what the,

402

:

the kind of the data is like

with people going in and out.

403

:

Yeah.

404

:

And we could see this natural sine wave.

405

:

So people going to work on a Monday

come home and it's just like sine

406

:

wave like this on the weekend

it would die down.

407

:

And there was one block in particular.

408

:

All of a sudden every two weeks

the the footfall would shoot straight up

409

:

and then back down again.

410

:

We thought there was something wrong

with the hardware.

411

:

We saw some of the kit,

but that was absolutely fine.

412

:

And what, what was going on in that block?

413

:

There was what we call in the UK, people

coming over, it's called county Lines.

414

:

They were dealing drugs from the block

basically.

415

:

So, from that data, we managed to analyze

416

:

a specific set of person information

which would flag this behavior.

417

:

So the gangs were coming over the border

from England, dropping

418

:

all the sort of drugs off

to be distributed from the block.

419

:

So, that was that was very interesting.

420

:

I believe these

that data in court as well.

421

:

Oh, that's red.

422

:

That's cool.

423

:

I'm sure that must have correlated

with when payday hits

424

:

because when the money's there

that's typical.

425

:

When it happens.

426

:

Yeah.

427

:

It was sticks in my mind that one. Yeah.

428

:

We didn't expect it.

429

:

Oh very cool Dean, thanks so much

for making the time and coming on.

430

:

It's been fascinating

to get to talk to you.

431

:

I'm super cool to talk to someone

who's been in the game for so long,

432

:

and just see how you've been able to use

433

:

LoRaWAN across the board for all these

different businesses. Thanks so much, man.

434

:

Thanks, Nik.

435

:

Brilliant. Thank you. Okay.

436

:

That's it for the business of LoRaWAN.

437

:

Thanks for listening.

438

:

If you enjoyed the show

439

:

and want to learn more,

the podcast home on the web is Mexico.

440

:

That's net SBI dot show.

441

:

There you'll find calculators to estimate

the impact of IoT usage on your business.

442

:

Be able to make guest suggestions.

443

:

If you know someone who

444

:

you think should come on the show

and easily get in touch with me.

445

:

If you think the show is useful

for LoRaWAN, please leave a review

446

:

wherever you listen to this.

447

:

Ratings

interviews really help podcast grow.

448

:

Finally, an enormous

thanks to our sponsor at the IoT

449

:

working Group at the Helium Foundation

for supporting the show.

450

:

If you want to try one out for yourself

without asking anyone permission,

451

:

you can sign up for a Meteoscientific

account at console.meteoscientific.com

452

:

and get your first 400 data credits

for free.

453

:

That's enough to run a sensor for

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

454

:

Right on. See you on the next show.

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The Business of LoRaWAN
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Nik Hawks

Incurably curious, to stormy nights and the wine-dark sea!