#55 - Nels Anderson: Bridging Air Quality Gaps – Middle Tier Sensors, Occupational Safety, and Technological Integration

Understanding the intersection of low-cost sensors and advanced environmental technology is crucial for enhancing air quality monitoring. The episode features an insightful conversation with Nels Anderson, who discusses the emergence of near reference grade sensors, the evolving role of occupational hygienists, and the impact of COVID-19 on air quality expectations.

• The significance of near reference grade sensors in occupational hygiene
• How low-cost sensors have changed the air quality landscape
• Bridging the skills gap with user-friendly technology
• Enhancing user experience through improved interfaces
• The shifting dynamics of air quality monitoring post-COVID

Nels Anderson LinkedIn

TSI

Chapters

• 0:01 The Future of Air Quality Monitoring
• 16:55 Comparing Low-Cost and High-End Sensors
• 25:56 Advancing Integration and User-Friendly Solutions
• 37:09 Advancing Technology and Enhancing Insights
• 49:49 The Future of Environmental Monitoring
• 1:01:09 Innovating Product Development for Diverse Users
• 1:06:20 Navigating Compliance in Environmental Monitoring
• 1:15:35 Revolutionizing Environmental Monitoring With Innovative Technology
• 1:21:53 Building Community Through Air Quality Partnerships

Transcript

Simon: 0:01

Welcome back to Air Quality Matters. I believe we already have the tools and knowledge we need to make a difference to the quality of the air we breathe in our built environment. The conversations we have and how we share what we know is the key to our success. I'm Simon Jones and coming up a conversation with Nels Anderson, business Director at TSI. Nels is at the heart of the health and safety products at TSI, a company with a rich history in innovation and cutting-edge technology. Tsi develops advanced instrumentation and software to measure and analyse the physical world with high precision. Its products range from particle counters used in clean room monitoring to air velocity meters and respirator fit testers.

Simon: 1:12

I was particularly interested to talk to Nels about this middle tier, near reference grade cohort of environmental sensors. Why? Because they bridge the world of low-cost sensors something we talk about a lot here and the world of academic reference grade measurement. In a way, they provide an insight into the technology to come and a window into sectors like occupational hygiene and health and safety. We discuss all of this the coming together of sectors and the blurring of lines to come, his journey into the field and much more. This is an episode full of insight and should be interesting to many of you. So thanks for listening. As always, do check out the sponsors in the show notes and at airqualitymattersnet. This is a conversation with Nels Anderson.

Nels: 2:09

So I'm more of a kind of a business and operational mindset when it comes to how do we use all these things, how do we create value for the customer, how do we, you know, bring it all together in a way that's easier to use. So, really, that's where some of our new products have come from is more about that workflow and how do we make it easier for less people to know more.

Simon: 2:31

Basically, no better person to speak to then, really, about my only question, I guess, which is we've seen this explosion, there's no other word for it. I think that, both because of the development of the technology, but also just the proliferation, compounded by covid, of low-cost sensors into the built environment, um, and there's no doubt they bring value, you know, I think it's well understood that they're enabling us, at a lower cost level, to get this kind of longitudinal picture of our built environment like we've never seen before. It's fascinating, which, for most people, most people haven't really seen that tier, unless you're in, like you say, in food hygiene or occupational health and safety and those kind of tiers. Um, I don't know if it has a name, but I kind of call it this middle tier, just below research grade equipment yeah um middle new reference right, what?

Nels: 3:43

whatever you want to call it right, but does it happen?

Simon: 3:45

I mean in your head, does it have a? Have a tier like, do you? How do you categorize it?

Nels: 3:52

the most common we we would use would be near reference methods um, that's kind of a common terminology that's used at least in the in the occupational space. Um, and environmental monitoring as well. Right, it's not. You know there is that tier that's the reference model, the BAMs and the T-Helms for particulates and things like that that are, you know, that are used for specifically very high-end research. And you know those environments where you kind of need to have exactly accurate measurements all the time and that's where, again, the market for that's fairly small, because not everybody's going to spend $100,000 on a piece of kit that's going to sit there and do one thing for a long period of time.

Nels: 4:42

So we play in that next tier down, really, or we historically have that's where our lines, like the dust track, have come in, and that's really about consistency, precision, durability and dependability in those areas where you really need to have really just ongoing confidence in that data being accurate for lots of reasons, but not least of which is the employee safety and liability side of the equation, right? So how do you make sure that you're protected? A lot of that has to do with compliance with regulations, right. Make sure you're protecting people in the best way possible in those high-risk environments. But you're right. Then it trickles down to well, yeah, but that's again if you're talking about the high-end research end of the market being a very small slice of the population, that next tier down is a bigger slice, but it's not consumer-grade for sure, right? So you're talking about still a very dedicated speciality of people that are looking at those types of instruments.

Simon: 5:48

But at the same time you've got all.

Nels: 5:50

Yeah, you've got all this movement in the market to. Well, there's less of those people, but they're being asked to do more and they got more data than they've ever had before. What are they supposed to do? Right, and that's where you get more into the. The low end easier to use, you know, more intuitive to operate, maybe more consumable from a sensor perspective, you know, rather than calibrating and maintaining it for a decade, you, you know, maybe buy a new sensor every couple years, right? So, um, so that's where you know you get down into that. Do I have a need, you know, as a plant manager, to monitor some things in between, when my IH can do it? Right, things like that. That's where you start to see it in the industry trickling down. And hygiene. Is people filling the gap between when they do their periodic assessments? Right, yeah, and that might be continuously based, or it might be a survey that they do with, again, a lower skill set staff member or something that can operate these things, or they can just place them in situ and leave them.

Simon: 6:54

You said there's less of those people. What did you mean by less of those people? Genuinely, are there less kind of the occupational, hygienist, technical people? Is that a thing?

Nels: 7:07

There's a challenge with sourcing people. You know there's not as many going through those programs at the university level so there's just a shortage, right, a lot of those. You know, occupational hygienists, industrial hygienists are retiring occupational hygienists, industrial hygienists are retiring. You know there's a lot in the baby boomer generation that, have, you know, decided to move on to the next stage in life, right, and so we just haven't. You'll see this too at university level and in a lot of industry groups that they're trying to recruit new people to be interested in this profession because it's just been slowly shrinking.

Nels: 7:46

So what that means also is, you know companies are also saying, well, I'm going to hire a safety tech, not an IH, and I'll give them a little bit of training and hand them a device and tell them to get going right. Which means, you know again, if they don't have a you know, postgraduate work in hygiene, it's got to be a little bit simpler to use, simpler to do reporting, simpler to analyze than it was in the past, maybe for somebody that has had a lot of training on these types of instruments. Or they might have an IH with a team of 10 safety techs across different facilities that they need to also train and enable teams these types of devices. So that's where, again, low-end sensing can help fill those gaps, where maybe you use them for diagnostics and triangulating, where you know point sources are coming from, and then you bring in an IH with high-end uh near reference equipment and do more of a deep dive in that, in that specific area, right yeah, listeners, the listeners.

Simon: 8:53

Ih is industrial hygienist, I take it yes yes, yeah, sorry about that, no no, we, I'm constantly, constantly have to try and remember. Sometimes we're talking to people that, um, don't know all of these acronyms, I'm as guilty as it is Next person, so try and remember I-H-R-O-H.

Nels: 9:12

If I use either of those, that's two persons, yeah.

Simon: 9:18

And it must be a fascinating space to try and figure out what next looks like. Space to try and figure out what next looks like because, like at the bottom up, there's that potential with better user interfaces and ux and low-cost sensors that we can, we can fill a void that I suppose at some point those professions were reaching down into and providing some insight on. Um, yes, but equally, at the same time you've got this supply challenge, as you say, because it's it's not easy to become an occupational hygienist or an industrial hygienist. I mean, there's serious qualifications. Like you, you really want to want to do it, like to go into that space.

Simon: 10:02

So I could imagine like a lot of engineering very hard to attract people out of pharma or computer sciences or some other technical thing that looks a bit more sexy at the minute. You know, industrial hygiene maybe doesn't have that pull.

Nels: 10:17

It did um, but it's your sense, even the talk of renaming, because of that right.

Simon: 10:23

Really, what does this even mean to?

Nels: 10:24

people. Oh yeah, that's a conversation that happens, right? Yeah, yeah, sorry, go ahead.

Simon: 10:30

No, I mean it's just, it's a sector that I think, unless you're in it and I'm not to be- frank it's not a sector there's much understanding of.

Simon: 10:41

Yeah, I can't imagine it's any less important of a job today than it was 20 years ago like we've got more technical built environments, more technical workplaces, more you know, like the old, the old sense of industrial hygiene and industrial health and safety. Like you know you might be, it would be silly to think that we've sorted all of those problems out, but people are still being exposed at an industrial level to pollutants. It's the same as they ever have been, haven't they?

Nels: 11:14

yeah, absolutely, and you know, and the role of the hygienist has expanded over time as well, right.

Nels: 11:21

So it's not like there's less work to do, but no, there there's just as many risk factors today and there's more understanding of those risk factors as well, right. So, for instance, heat is a big one that receives a lot of attention. Now, you know the complexities that come along with managing heat stress. That's a little off topic, but you know there's new work going on combining particulates and heat stress together and the impact that has on people, right, and their health when those two things are co-located. In the past, those things were monitored separately, right, but now people are starting to say, well, what if we monitor them together and assess what the risk factor is as a combined risk rather than separately, right? Singapore has rules about this, for instance, that they have to do this type of reporting. So those are things that are happening too, where the multifaceted, multivariable risk assessment is something that's emerging and the hygienists are being asked to do this, and yet there's less of them to do it. So how do we provide the tools to enable that to happen?

Simon: 12:28

yeah, and to to kind of place where tsa tsi's technology comes into that space. These people, these, these technicians of our built environment, hygienists of our built environment, are often working in a world, if I understand it correctly, where there are tolerances and thresholds of certain risks that need to be measured Anything from noise to air pollutants, to exposure to chemical, all sorts of things, to chemical, all sorts of things. And in that and in that world, uh, a hygienist is being asked to give an opinion based on detailed tests and measurements and approaches and well understood processes, on whether somebody is above or below that, a lot of those lines. You know that your exposure values and whatever the terminology is. So it's a precise world and a complex world. You know you're going in to your. Your result and your answer means something.

Simon: 13:36

We're not just giving a fluffy warm like this is a healthy building, like you have to. You have to give hard numbers in that world, don't you? So you need equipment that can get you as close to that hard number as possible yeah, and and especially those hard numbers have to be in the right location, right.

Nels: 13:57

So, as you can assume, you know a huge industrial facility. There's a lot of different things going on there. There's no way that they're going to buy 40 of our dust tracks and sit them in every possible location and figure out exactly where things are coming from.

Nels: 14:13

They have to have the ability to kind of map out where the hot points are for any risk, right, and then figure out what to do about it, what type of mitigation they're going to go for and that's again where an ecosystem of lower-cost solutions helps out, right, so they might be able to then place multiple low-end sensors around a facility, triangulate where they think the point source is coming from and then really focus their efforts with their limited resources on that area, versus, you know, kind of doing having to do a little bit of this based on, you know, observation and expertise to figure that out today, right, which is a lot of times what happens and you talk to a group of IHs and they're going to probably say that, you know, yeah, I have to take a gut feel approach to get started in a lot of cases, right, because they don't have the ability or the time or the tools to do a holistic assessment of every single possible risk factor.

Simon: 15:14

Yeah, I had Brad Prezant on the podcast earlier in the summer and he's an occupational hygienienist one of the few actually with an indoor air quality specialty and he was saying you know, in in some environments you know, you know what you're looking for for before you even go. It's a particular industrial process and you're you're checking against dust levels from wood sawing or whatever it is like. You know it's a pretty given environment but sometimes it can be very general, that kind of general workplace sick building type. We think something's wrong with this space. We don't really know what it.

Simon: 15:55

There's some real skill and nuance to that, that, that approach you need to, like you say, maybe deploy, deploy lower cost sensors, do research and questionnaires and spend time figuring out what the sources could be. As he said, often you walk in the door within five minutes. You know what the source is before you even get up the stairs, but sometimes you don't. It can be quite fluffy and grey and nuanced and that does require some skills and experience and expertise to unpack um. And that's really where I guess, with tsi, its ecosystem really facilitates that. It's that ability to deploy a range of solutions to start unpacking the problem of that, the space that's right, and, and you know it's always, always there's a desire for this.

Nels: 16:48

Hey, can't you just give me a, you know, a product selector tool that allows me to easily choose, uh, you know which one is right for me. And you know, question is kind of sort of maybe right, you know the answer to that is uh, because there's so many different dimensions that you could go down. It depends on what you're trying to do, right? So are you going to, you know, be doing this continuously? Are you going to be doing this inside or outside? Or are you going to be doing this for compliance reporting? Or is this more indicative, so you can make sure your employees are happy? But there's no high risk level threshold that you're dealing with? Or are you trying to do something in a very high concentration environment that's going to drive you down a certain technology path as well, because some sensors just aren't going to work or live very long in some environments, right? So, yeah, it's a very complicated question to figure out which part of our portfolio, or any other provider's portfolio, to use because of all those different. It's not even a Rubik's cube, right.

Simon: 17:54

It's a dodecahedron cube or something that has so many different variables to it yeah, and I encourage anybody to look at the tsi website and just see the the sheer breadth of technology that's on there. Um so like, even if, even just thinking of something like ventilation and air quality, there are four or five verticals of products that you could be having to look through, just just within that question never noise and thermal comfort and other things as well, um, absolutely I mean it's a it's kind of the elevator explanation for listeners.

Simon: 18:30

What's the fundamental difference between a low-cost sensor, an AirThings Katera Imbiote-type device that people might be familiar with, that on the face of it is measuring CO2 and particulate matter, and maybe even some of the electrochemical sensors might even be doing CO and ozone and some other stuff. What's the difference between a five or six hundred pound low cost sensor and, when you start getting into this near reference grade equipment, what fundamentally separates the two? Is there a way of describing that?

Nels: 19:09

I think you know. One is what, what is the load they can handle? That's's definitely a big part of it, right? How high of a concentration can that sensor reliably measure? Another piece is calibration, right. Is it able to be maintained in the field and be credible for a long period of time? Or not? Right, or recalibrated if it needs to be? The other part is, you know, the part of the ecosystem. Is it a standalone, right? Is it kind of sit there and it measures that one thing continuously, or do you need it to be part of a broader data set? If you will, so it's connectivity.

Nels: 19:50

Analysis and reporting, then, is what you also need, right. And then the you know just, the accuracy of the measurement itself. So, even in you know, the low cost sensor space, there are some sensors that are going to be more accurate than others, right. And then you move up to, or precise, depending on how you're referring to it. And then you move up to, you know, those higher end types of, you know, laser optics based measurement devices which can have, you know, reliability. It's very tight to the reference method for long, long periods of time, right.

Nels: 20:29

So that's you know. How much variability are you okay with in your process measurement, right? Or how much do you need to depend on that exact answer, right? So if you know, if you're measuring a, you know inside a, you know outside my door here in a cubicle environment where maybe plus or minus 5% for some sort of comfort index is not going to make a big difference to the team. But if you're in a manufacturing environment where plus or minus 5% in silica exposure is going to make a big difference because you're going to be over thresholds and people need PPE and things like that, that's where you see the change it depends on that application.

Nels: 21:13

How big of a swing can you take in a short period of time?

Simon: 21:18

so so there are several parts to it.

Nels: 21:20

Then, if I understand correctly, there's the yeah it's not, it's not one answer, I guess yeah yeah, yeah, sure challenge, yeah, yeah, as as with all these things.

Simon: 21:29

so it's a kind of a. There's a hardware question Is this sensor significantly more accurate or does it in a different way to a low-cost sensor? So there's the physical differences between the approaches of measurement or the accuracy or device and, as with all things, there's a trickle down in cost and accuracy with this tech, all the way from reference, all the way down.

Nels: 21:54

And that ties to durability as well. Right, is it. Is it one a one year sensor, you know consumable, or are you going to have this thing for a decade?

Simon: 22:02

right, that also plays into that and that's the thing. It's that process driven. This is a tool that somebody has to use that can give an accurate or an act within a tolerance result, the same on that six months as it does at year two, as it does at year five. I mean, this is a a piece of equipment in the hands of a professional generally who needs to be able to work with that tool and understand whether that's infield calibration, that you take elements of it out and replace it so many times a year or whatever the, you know the, the pressure it comes under because of the environments. It's in that there's an approach that means I can stand over a degree of accuracy the same on six months as I do at year one and year three and year five or whatever it is.

Simon: 22:49

So it's a. It's a that long-term reliability. That's as I was talking to maria for goals from immbia there the other day. The reality is we still don't know. With a lot of low-cost sensors they haven't actually been out in the field long enough to really know what the drift is We've got some idea with some of the earlier sensors, like CO2 and temperature.

Simon: 23:10

We've got some sense, but what the 10-year lifespan of these pm sensors and electrochemical sensors? Like we really we we can get an idea of the the degradation curve over time. We can forecast, I guess to some degree, but we don't really know, whereas these devices that you're talking about have been in the hands of people year after year for a while now and they need to be able to stand over those devices year after year. That that's the fundamental difference, isn't it that that this is a, this is a piece of equipment. When I walk into a building and I'm creating a report, I need, I need to know that another hygienist could come in six months later and I can stand over what I've said effectively Exactly.

Nels: 24:01

It's the confidence in that data right is what's critical.

Simon: 24:04

Yeah.

Nels: 24:06

And again, not taking away from any. You know we use sensors in some of our products, right, that are on that lower end of the scale. But the key is to know when you have to do something about it. Right, how often should you be replacing them? How often should you be calibrating or servicing, if possible, most of them, or replacing service? But you know that's critical as well, right? How confident can I be that this is doing as good as it can do in this environment that it is being put into?

Simon: 24:38

yeah, that's a really interesting point actually, that there may actually be not a massive difference in the technology, the hardware, but it's, it's, it's installed or part of that system or ecosystem in a way that you might treat it differently, that you might replace it every year, or that you can calibrate it in a particular way in the field that you wouldn't be able to with a low-cost sensor.

Simon: 25:02

That so it can be a fun. It can be a fundamental difference in use rather than tech. I guess yeah, okay, yeah, and I'm guessing you've seen a change over the last few years then in the whole kind of UX user interface experience with this hardware as well, because I imagine it was fairly rudimentary five years ago or so that poor sods were trawling through large sets of Excel data sheets trying to cobble stuff together, sets of Excel data sheets trying to couple stuff together, whereas the last time I was with your guys on a stand in an exhibition somewhere, it was all getting a lot cleaner and fluffier for people to navigate and look at. So you're involved in that same as everybody else is. The whole UX UI experience for users is improved.

Nels: 25:52

Yep, absolutely. I mean, I think it's. You know, gone are the days where you know you build a product and you have a UX and UI design for that one product and then you move on to the next product and that one starts from scratch. Right, but everyone's got these right. So how do you make it simple to use? And so it's. You know it's used to what, it's similar to what people are using in their daily lives, right? They're used to having very easy to navigate interfaces, very easy to create different types of views and reports and things like that. And at the end of the day, you know if you're an industrial hygienist or you're a facilities manager, you're trying to get your job done, and the more systems you have to use, the more data sets you have to manage you know, that's just more time out of your day.

Nels: 26:44

That's being wasted, right. So how do we bring it all together and make it easy for that person to do the jobs, the workflows they're trying to get done, rather than making them learn 10 different instrument interfaces to do 10 different measurements? So that's a lot of the focus we've been putting on the last year and a half or two in new product development is helping to bring data together, bring user interfaces together. So that's a homogeneous solution set rather than very disparate.

Simon: 27:18

We see that across the sector, this kind of apple approach where it doesn't matter what your entry point into the ecosystem is, your experience is largely the same, that there's this familiarity in appearance and use and buttons and how you express data. All of that has. That has a cohesiveness, I suppose, for want of a better word that means it makes it familiar. The interesting thing about that, I think, is that it blurs the lines much more with use of those systems, whereas before there were only a handful of people that understood how to get the data from a TSI piece of equipment and turn it meaningfully into a report. Right, and that was the occupational hygienist and so on.

Simon: 28:03

I mean part of that strategically, I guess, is a business as you broaden your market because all of a sudden less specialist people can gain insight where they wouldn't have been able to gain insight before. And I know I see even in the hardware a blurring of the blurring of those lines. So you have like your omni track system now, which is kind of starts to look somewhere between low cost sensors and this near reference. It becomes much more user friendly and everything's easier to deploy and so like. It's good because it broadens the market but it also makes it I suppose in some ways takes some of the um, the specialism away from those specialists that all of a sudden facility managers and people with good basic technical experience can gain some insight where they just that wouldn't have been available before.

Nels: 28:58

Yeah, absolutely. I think I'll use a quote that one IH, at one of our local chapter meetings said. He said, well, don't make it too easy, no, because he's a little afraid of everybody. You know, he's a consultant, right, he doesn't want it to be too easy for everybody, but at the same time there's, like I said, there's a resource shortage in this area. So you know, we'll talk to someone that's running a manufacturing plant and they'll say, look, I only have my IH consultant once every two months coming into my plant. I can't wait for two months to find out if something's going wrong. So at least this gives me, you know, something to use in the interim.

Nels: 29:36

I'm not professionally trained in this area, but I can operate this thing right. I can use these types of sensors, I can deploy them and at least have somewhere to point my professional to when they're here, right? So at least to check something out or know if a trend line is going up, right. So that's where we see this as well. So some of it is let's make it easier for the professionals that do this every day, and then some of it is, you know, for those that can't have a professional in their facility every day. How do we fill the gap right and bringing all the data together right? So even you know, the tongue-in-cheek comment from that professional is like, yeah, but if I can actually do this and also bring my dust track data into this same ecosystem, that helps me a ton. So this is, this is great, which is you know.

Simon: 30:22

The next step is bringing legacy data in to the same ecosystem with these other lower cost sensors yeah, and I bet there's very few specialists that actually enjoyed the, the data collection and the the writing of reports, right. So what we're a, what you're enabling them to do, is do the good stuff more and the boring stuff less. You know, the, anything that stops it becoming an eight-hour reporting writing exercise? And all of that stuff is consolidatable and producible automatically. You know, unless that was your bag, which there are people that love, that stuff is consolidatable and producible automatically. You know, unless that was your bag, which there are people that love that stuff, but most people don't relish the report writing day.

Nels: 31:03

I'm sure so anything that speeds that up, yeah yeah, yeah for sure.

Simon: 31:10

So what is that kind of where you see the the direction of that industry, then just generally going just the blurring of lines out into more technical disciplines, with that data set and tools and equipment that increases your market and speeds up and facilitates the specialists, the occupational hygienists and industrial hygienists and makes their life easier. Is that the kind of general trajectory you see in the sector? I think that's true the occupational hygienists and industrial hygienists and makes their life easier. Is that the kind of general trajectory you see in the sector?

Nels: 31:38

I think that's true. Yeah, I think. Uh, you know, in general, like I said, their, their role is expanding as well. Right, so 10 years ago they might not have had to do anything, reporting on esg, for instance, but now they, they do they have to feed information in on, you know, environmental risk factors into those environmental social governance reports and things like that.

Nels: 32:01

So as they're expanding into those other types of responsibilities, they've got to find time somewhere. So a lot of that is how do we make the workflow, the one or two days a week that they spend writing reports behind the scenes? How do we make that one day, four hours, whatever, it is right, so that they can actually spend time on the more value added things that are, you know, training people and intervening?

Nels: 32:25

in the risks that you know might actually harm people every day. So, yeah, I think that's true. I think that's, in general, also what you'll see in the industry, not just at TSI. Right is people working towards? How do we make systems integrate better? How do we get data sharing across different systems, integrate data from one to another? All those things just like you've seen in any other part of the market.

Simon: 32:53

And looking downstream at the kind kind of the low cost sensor market, do you keep half an eye on that? And I mean, I know you've got I wouldn't call it a low cost, it's a really good multi-sensor that you do. But, um, do you keep half an eye on that section and see what's working and what isn't, are you? Is there stuff to learn from the bottom up for you in that tier that in usability?

Nels: 33:18

absolutely, yeah, um, and again, you know we're we're all consumers as well, as you know, working in our business during the day, right. So, um, you know people, as people get used to having integrated sensors in their homes, right. Then then you start to expect or look for opportunities to manage businesses that way as well. So you know we do play in some of that space today in indoor, air and outdoor environmental monitoring. You know, like you said, we're not at the lowest end of the spectrum, but we do see.

Nels: 33:51

You know, when you're looking at this continuous monitoring market, there is opportunities for businesses to do better and to learn more about what's going on in and around their buildings.

Nels: 34:01

Yeah, and you know that means you have to have a lot of them out there, which is a different model than one person carrying a few devices around Right than one person carrying a few devices around right. So you know that's where you have to be looking at that low-end sensor market and seeing what's working, where scale is happening, because that's going to enable you know that network effect of that data. If we can get, you know the population of sensors out there across our customer sites. You know they start to see the trends across different geographies, across different manufacturing types, and again able to analyze that in a better way. Whereas before it might have been based on one person doing a survey once a year, now you can see things happening in real time and do something about it in advance, rather than waiting until somebody happens to come upon it or there's a citation or somebody gets hurt God forbid. So there's definitely always going to be a view of that part of the market.

Simon: 35:11

Must come back on to the somebody's going to get hurt, because I think it's an important piece, um, but I think one of the fascinating things about being in the middle tier I mean I know you're not just in the middle tier, don't get me wrong, right but I think one of the interesting things about being there is you see what's happening above and below you from a technology perspective, um, we've seen in the low-cost sensor market. You know we're starting to see electrochemical sensors start to do a better job. There's a lot of caveats to that still, you know and understand, but that's quite exciting to see. You know, I've just been seeing from a low-cost formaldehyde sensor in my office here doing a pretty good job. You know I've just been seeing from a low cost formaldehyde sensor in my office here doing a pretty good job. You know, differentiating and not a lot of cross sensitivity and starting to get interesting now for the first time.

Simon: 36:10

Sector, looking up what. What should we be excited about? Do you think that's trickling down now when it comes to hardware, calibration, software, like, did you see some interesting developments or lessons you're learning that are starting to trickle down into that sector?

Nels: 36:33

that's an interesting question. Um, I guess I would. I would say if, if, like what you're saying, if speciation gets good enough where people can count on it. Um, I think that that's interesting, right? I think, um, you know the ability to distinguish specific gases very accurately. You know there's a reason that people have to take samples of you know of these risk factors today, right, because that's the only thing that, compliance wise, is trusted, right? So, so, those types of things.

Nels: 37:09

If that technology advances, I think that the market would embrace that. Other than that, I think it's all about the analytics, right? What are we going to do with all this information that's coming at us now, right? And how do we look at them? In combined ways, rather than just right, wrong or indifferent. A lot of people are laser focused on a specific solution, and even at TSI, right, when you look at things combined together that you'd never. You always had the solution, but you never combined them before you learn new things, and I think that's where, potentially, the low-end part of the market could see us going right.

Simon: 37:52

The thing I'm fascinating to see trickle down from the middle tier is the understanding on long-term usability of products and calibration. I think there's a lot of unanswered questions generally in that space. We're seeing a lot of subtle shifts with standards like Well and others trying to wrap their heads around that to some degree. Um, because, a the technology is moving forward quite quickly but b so there's more trust, I think, than there would have been even five years ago in some of the stuff that they're seeing um, but there's a lot of dangers in that as well, and so I think that for me is the interesting thing. Is there some well understood routes and pathways that the middle tier can trickle down to the lower tiers about how we stand over the long-term accuracy of these devices or find practical ways to understand the limitations in those spaces? Because you've had to work through that years and years ago.

Nels: 39:02

So yeah, I'm sure it's quite to begin with, but yeah yeah, I mean you have to have confidence that that data is that is, you know accurate for that application. I'll call it right, you need to have how much variability am I going to allow for this specific application? And then, if you know you might be pushing the limits of that application with your technology, then you have to deal with it, like I said before, from a process perspective. Well, the sensor's only going to be good for six months in this type of application, so we're going to have to pull it out and swap it out every six months, right, those types of things can be done.

Nels: 39:42

But then it gets to be the clunkiness of the solution, right, comes into play. And does that mean I pull it out and recalibrate it, or does that mean I have to send it in, or does that mean I throw it away? Right, all those things are an option. But, yeah, at least the occupational market is going to require that. It's just there's no way around it, right, you have to be confident that that data is saying I'm going to be okay by putting people in this environment, or I'm going to be okay putting them in this environment with personal protective equipment, or I have to do engineering controls or whatever, but I need to be confident in that data to start with in order to develop that action plan right, and that's where you can't have too much volatility in that data.

Simon: 40:28

Yeah, and I think one of the interesting things we'll see from the no-cost end is an evolution of the customer base as well. To be fair, most of the sensors have been deployed to date in flagship buildings, so mostly it's been an exercise in just rubber stamping what was always going to be a good environment anyway. But as we increasingly see the deployment of these sensors into the broader, longer tail of real estate and non-residential spaces and residential, to be fair we'll start to see more problem buildings and there it's about understanding what the purpose of those sensors are. It stops becoming just a rubber stamping of. This is a well platinum building to workflow generation like what, what? What's the actionable insight from the data that I'm seeing, and I think that's interestingly where there's going to be more demand, I think potentially downstream for these professionals.

Simon: 41:32

Because I always use the analogy and I have to come up. You might be able to help me with a better analogy for the middle tier, but I've been kind of using this analogy of the low-cost sensor market as kind of the health wearables of the of the medical market, in that they tell you patterns and some interesting things about your heart rate and your sleep patterns and maybe even your blood pressure, but at some point you're going to need to go to the doctor to get a blood test and an ecg and like to find out what's really going on right. So health wearables have always been about providing you with actionable insight to do something when you need to, or telling you that everything's great. Most of the people that wear health wearables all bloody healthy, you've noticed right so it's a bit like that in the built environment.

Simon: 42:21

So it'd be interesting, like the occupational hygienist is kind of your general practitioner of the built environment. That's my kind of loose analogy. Um, so I'm wondering where the middle tier sits in this broad health analogy that maybe it's your fitness coach, has professional equipment that actually does your blood pressure, that's calibrated or whatever it is you know, or can take an ECG and something right. There's these middle tier of practitioners that have a more detailed understanding of the data that they're looking on, beyond what you're wearing on your watch, that can provide that insight I think that's a.

Nels: 43:03

I think that's a good analogy. I think, um, you know, some of those practitioners might argue they more, know, more than the doctors actually in some cases. But uh, but, uh, but no I think.

Simon: 43:15

I think in both analogies that's true, yeah I think you're right.

Nels: 43:18

Yeah, um, so you know, because they they use that equipment more every day, or whatever. It is right, so, um, but yeah, I think, I think that's fair, I think there's, you know, and then at some point you got to escalate to that mri machine, right, and you've got to go all the way up and get the high end.

Simon: 43:38

Yeah, all the way to the consultant, yeah, at some point.

Nels: 43:40

Yeah, exactly. So I think that's fair. And again, even in that middle tier, where you're a general practitioner, they've got a lot of patients to see every day, right? And so how do they enable the workflow to get through all those patients? Right, and it's kind of the same problem, right, we need to make sure that we're providing efficiency throughout that day so the high value added items can be addressed and and not the low value ones. Right, we're just getting done and off the plate yeah, that's really true.

Simon: 44:12

And sitting in this middle tier, are you seeing stuff coming down from the reference grade end of things? That's exciting and pushing the development of this near reference tech. Speciated PMs, speciated chemical compositions I mean you go to the very top of the tree and there's some fabulous equipment, as long as you've got a couple of millions to spend on it.

Nels: 44:38

That's some money yeah.

Simon: 44:41

But nonetheless there's some very exciting tech that I'm guessing no doubt will trickle down in some form or other.

Nels: 44:48

I'm sure I mean, as all technology does right, you look at a new application and use it in a different way. All technology does right, you look at a new application and use it in a different way. And even at TSI we have, you know, some other divisions that are working on some high-end, specialized stuff for, you know, clean rooms and things like that, so you never know what's going to come down the pike, but I think you know it gets to.

Nels: 45:14

What market are you trying to serve, right?

Nels: 45:16

And there's that research arm that's always going to be needing the high-end equipment or those highly at-risk products that you need that type of equipment to manufacture.

Nels: 45:29

And then you know the majority of the market is going to fall into that next level down, right. The market's going to fall into that next level down, right. So I think the key thing for us is you know how accurate is accurate enough, right? And is that going to change the action that you're taking in that application, right? So, to your point, you know, if I find out that you know I'm plus or minus 1% on you know my blood pressure, that's not going to change my diet, probably, right. But if, if I am, uh, you know, plus or minus 10 on a credible piece of equipment and, uh, I spiked all of that within the last month, I probably did something that I shouldn't be doing and I need to work on it, right? So how do we make that, you know, alerting on those types of things very easy? How do we make diagnostics of exceeding thresholds very easy, so that people can take action and actually do something about it, versus just well, here's another report, put it in your pile and hopefully we're better next time.

Simon: 46:38

So that action is the key. Yeah, I suppose a little bit. The difference between the lower tiers and the middle tier is a sense of perspective. A lot of the lower tier stuff has been driven by the art of the possible We've been putting because we, you know we can. We can now measure pm, so it's in there. We can now measure formaldehyde, so it's in there. And then learning and developing how to get that cost down and find innovative ways to to generate actionable insights from something that has less tolerance of accuracy than perhaps the middle tier does. But it's a. It's a fundamentally different approach. It's about trying to find ways to create value out of that tech, whereas I'm guessing in the middle it's, it's almost flipped. You're trying to deeply understand the needs of a particular process or profession and cultivate a solution that answers as best as possible that need, like it's uh it.

Simon: 47:41

Whereas the low-cost sensor has just been about technology development primarily. Push, yeah, whereas this is about process drip. Pull, isn't it the mid-tier?

Nels: 47:53

yeah, and sometimes that the technology is going to fit in that process and sometimes it won't right, and try another one, right?

Nels: 48:00

um and again, it all comes down to the specific requirements that are going to meet the need of that specific market segment and application and you're not going to be able to fit, you know, every single uh sensor into that, every single application. So that's, that's why you have to have a broad solution set, because every you know, monitoring things in a mind it's much different than monitoring things, uh, you know, a health care or uh, it's just, you're never going to use the same equipment in those two situations, right?

Simon: 48:32

while I have you, I just want to briefly talk to you about ultra protect, a partner of this podcast. Look, they're not here by accident. Like the podcast, they are passionate about driving changes in our indoor environment and are an all-round great company to deal with. Ultra Protect provides cutting-edge technologies and services focused on air quality and dust management. They have years of experience in the industry and a team of people I have leaned on on many an occasion for advice and insight. From continuously tracking air quality to specific sampling, they analyze and provide actionable insights in the built environment. Specializing in dust management, they provide amazing products and services that minimize risk and improve environments, from construction sites to offices, to manufacturing settings, through to solutions around ventilation aimed at improving the environment in the long term. It's a company well worth checking out. There are links in the show notes on airqualitymattersnet and, of course, at Ultra Protect UK. Now back to the podcast. Maybe explain to people a little bit about TSI. Have you drunk fully from the TSI Kool-Aid at this point Like are you fully TSI?

Nels: 50:01

I'm three years in.

Simon: 50:03

Three years in. Okay, Maybe not completely yet, but it's got a fabulous history, TSI in this space, doesn't it?

Nels: 50:11

I mean, it goes way way back, yeah, yeah, so in this space I don't even know when the first invented technology was, but it basically founded on detection technology similar to the base technology we're talking about now. Right, it was the main founding product for TSI back in the 50s. But even and then Casella, our counterparts across the pond they go all the way back to the invention of the mercury thermometer, with Charles Darwin as one of the first customers, right? So huge amount of measurement expertise on both sides.

Nels: 50:49

But yeah, I mean again this is a foundational part of the core competency of TSI is how to measure small things very accurately, right? That's the basics of it.

Simon: 51:00

Yeah.

Nels: 51:02

And do it in a way that allows it to be applied in a use case in industry, right?

Nels: 51:07

Not just in a lab, right. So you know, we continue to push forward on new ways to do this. But, again, a lot of times we're looking at technology that's happening outside and we do, you know, technology development inside and see how they match up together, right, and you brought up Omnitrack earlier, so I'll bring that up. It's, you know, the core technology is really about, you know, leveraging some sensors that are, you know, are well-known in the marketplace and some that are proprietary, and also bringing in the ecosystem of the rest of the TSI information from other instruments. It's really about how to make it all easier to use together. That's a lot of our focus right now. Is the UX UI experience that takes. Maybe we'll invent a new photometer in the next year, maybe we won't. It just depends on what the application needs. And is that difference in that technology going to add value to that end user or not? Or is it more important to work on other things?

Simon: 52:15

right, that interface and data analysis and yeah, what do you think pulls people to tsi above, above, above others? I mean, what's its, what's its dna that that effectively is that makes it the market leader in this space?

Nels: 52:35

I mean, I think we've talked about it a lot of times on this call, but the confidence in that this information is going to be accurate, that I can rely on it, that we're going to have durability so that I can leave this thing in a harsh environment for a long period of time, and it's going to continue to kick out the right information.

Nels: 52:58

I think that's a big thing we hear over and over when we talk to people oh yeah, I've used that thing for 10 years. I guess I'll get a new one, but you know, it's very much a confidence in the data. That's what people are interested in. Take that worry, I guess, out of the equation, right? Because when you think about it, you know most of our legacy users are. They're not, you know, like this, sitting in an office environment. They are out hitting different facilities, they're on the road, they're doing different things.

Nels: 53:30

If you lose a day because your equipment went down in, you know, in Cincinnati and you're supposed to be in Columbus the next day, that messes up your week, right. You're not able to move on to that next visit, the next consulting job, whatever it is, because your data set was messed up and you have to start over, right. So that's very important is making sure that it's dependable, it's reliable, it's accurate, again for that specific application. And then, if you're needing to do multiple different parameters, that you have a tool set that allows you to do that too. You can expand and meet the need as you identify risks. So that's another part of the Tsi uh proposition, I guess, is that we have a very broad portfolio of solutions I must look up your tagline, but it must be something like we measure lots of stuff really well.

Simon: 54:27

Basically, I think that's what. I think that's what's hard to appreciate for a lot of people is that there's an escalation of environmental risk and at some point you've got to be able to put a hard number on something.

Simon: 54:41

Like it always gets there, you know, like when these, when these work processes escalate over time, at some point you've got to stand over something and at that point it usually ends up with somebody holding a blue piece of equipment, wandering around deploying sensors that you can stand over that number or sending sample tubes off to a lab or something you know like. At some point it ends up there.

Nels: 55:08

That's the challenge it does, and that's really what the industry is learning how to uh differently now, right, and you know people have not had. You know this is a pretty nascent technology in this market, right? So they haven't really figured out. How do I do things differently if I could deploy 50 of these things in a location at once, versus doing my normal? I'm going to stop in, I'm going to do some observation and then I'm going to put one or two units in certain locations. So that's something the industry is still learning is how to best do that. Again, it'll evolve over probably the next three to five years as people do more case studies and researchers learn more things.

Nels: 55:53

But to some extent, you don't know what you don't know yet. It seems like the right thing to do that. You can monitor risks over time instead of waiting for the next cycle of periodic assessments, right. But again, people haven't figured out exactly how to do that best. Yet. You go to any conference. A lot of what people are talking about is how did I do this study using distributed sensors? How did I do my analysis in a different way, using statistical modeling, all those things? Because in the past, if you only had a week's worth of data from one instrument. That's a different assessment than if you have 50 sensors for a year.

Simon: 56:29

Right, you gotta look at the different way and I think that's what the I think that's the big learning exercise the industry, the broader built environment industry, is going to have to go through with this explosion of low cost sensors. And I think Joseph Allen hints at this at some point in one of his books where he says you know, the risk is, with the world full of APs and kind of general practitioners in the space, there's a risk of giving an opinion that a building is healthy, right, at some point you need the qualifications to be able to say that and the data, the reliable data, to stand over that decision, because at some point it's whether or not that healthy building or that tolerable risk to use health and safety parlons. At some point somebody's got to be qualified to give that opinion. And I think we've expanded healthy buildings out into such a broad portfolio. We're giving very generic health and well-being expletives about the space.

Simon: 57:41

But as a business owner or a process owner or whatever it is, at some point you've got to be able to say, yes, this is, this is an acceptable risk, or this is a tolerable risk, or this is a healthy space, or whatever it is. And I and I I think we'll always just end up there. I was hearing a presentation by the world building standards there a few weeks about talking about. They were kind of backing off this need for annual air quality assessments and relying more and more on on low-cost sensors. But even they were saying that they at some point you're still probably going to need somebody to come in and give an opinion. Ultimately.

Nels: 58:24

If nothing else, to validate that those sensor ecosystems are still saying what they should be saying, right?

Simon: 58:32

Yeah.

Nels: 58:32

Validate that data.

Simon: 58:35

Yeah, and I think that's the challenge. I think somebody that's coming at it from a process perspective and understanding the limitations of low-cost sensors is going to be hard pushed to be able to give an opinion. It will be part of the toolkit, but I can't see it ever standing alone. It might generate certain workflows as, like you say, might show sources like, start to develop a pattern of where sources might be coming from. But ultimately, at that point then you're going to want somebody coming in, and that'll be the interesting part. And god knows how we're going to do that without enough occupational ideas, to be frank.

Nels: 59:15

Yeah, well, unless we can invest that shortage.

Simon: 59:18

Yeah, maybe there's a whole new tier that needs to pop up somewhere in between them. I, I don't know, but like somebody's going to have to do it and it's not going to be the people that are managing the low-cost sensors. You know, it's not that level. It's not a accredited professional kind of level, ap type level. It has to. I think you're going to need some kind of degree qualification to be able to give an opinion that you, because you won't be able to get the professional indemnity to say something meaningful. I think that would be the hard reality. You know you couldn't get the professional indemnity to stand over a healthy building as an AP. Frankly, that makes sense.

Nels: 1:00:02

You know it all comes down to insurance eventually. Liability yes.

Simon: 1:00:08

For sure, yeah, for sure. How did you end up in this space? What was your kind of journey to here and to your side?

Nels: 1:00:20

Yeah, so I mentioned I was kind of in the in the food safety area. So I was at eco lab for a long time almost 11 years uh, managed a lot of different segments and verticals there but really, you know, ended up in kind of the beverage and brewery processing uh segment there for for quite a while and then was asked to kind of step in and take over a digital offering that we were putting together. So kind of moved from that consumer you know cleaning and safety products to how do we take the data that's happening in all of those you know facilities around the world beverage and brewery manufacturing facilities and help those customers do something with that information to produce more efficiently, safer, healthier, better resource conservation, all those things. So that's what I did the last five years. So when I was at Ecolab. So it kind of moved more into the digital side and then moved over to a healthcare startup, again on the software side, and then moved over to a healthcare startup, again on the software side, and was there for a few years to help grow that business.

Nels: 1:01:22

And then TSI was kind of looking for something that combined the two, something to help bridge the gap between the future software and UX solutions and the hard goods legacy, the hard goods, uh, legacy products. So that's the reason I came, um, yeah, so, yeah, that was my transition, but again I was, you know, never, never a health and safety specific. You know, uh, classically trained hygienist or anything like that, um, but had kind of my toes in the water, been in a lot of manufacturing facilities globally and you know learned on the road doing that and then when I came over here, learned through all the expertise we have at TSI and talking to folks in the market.

Nels: 1:02:07

So that's my background.

Simon: 1:02:09

And today again your job title, your role is in kind of product development principally.

Nels: 1:02:16

Yeah, it's business director, which again is in kind of product development principally. Yeah, it's business director which again is kind of a it's a, it's a cross between I'd call it at other organizations a kind of a vp of product and a division manager, if you will. Yeah, so you have pnl responsibilities for the division, but also you know product and new product development responsibilities.

Simon: 1:02:41

I mean, I've always been from a commercial background and I think the interesting thing about having one foot in the sales pipeline, as it were, is that it sharpens your pencil when it comes to product development and having stuff that's fit for purpose and does actually create value for the customer, which is what this is all about. I mean, none of us make your case blue boxes for the fun of it. You know like it's, it has to have value, so it's that. And that's where the bleeding edge of this stuff is. I think is in that ux ui value generation for the customer piece, because the technology will move as forward as it does. But but there's some real innovation isn't there? And how we take that data and that information and present it in ways and do stuff with it and create ecosystems with it that has value. Um, that I imagine is quite fascinating in your sector because you've got so many different types of customer like how you do.

Nels: 1:03:44

That must be fascinating fascinating is one word, uh, challenging is another yeah, yeah, um, but no, you're right.

Nels: 1:03:53

I mean, if you think about you know, uh, I'll just pick one of our other products that people might know, the Port Account, which is a respiratory fit testing device. One user of that might be a registered nurse in a hospital. Another user of that might be an IH giving doing fit tests for a company. Another user might be a fire department, you know chief, or someone he delegates to do the testing. Another user might be a police, you know captain that has to do it, is assigned to do it, right, like very different in terms of background training. It's got to be easy to use for everybody, right, because it's not going to be used by the same type of trained person everywhere, right? So that's you know.

Nels: 1:04:38

That's just one example of, yeah, if you're looking at, you know we sell to almost industry, every industry out there. You've got to think about it from the end user's perspective on. You know where are they coming from, when they're going to use this thing, right? And again, a lot of our products are designed for that high-end user with a lot of training. But as we move forward in this market, you've got to think about that broad swath of users that just needs to unbox the thing and use it without having a lot of training. So yeah, a lot of work to do there, a lot of opportunity, definitely to make it easy to use, easy to analyze, easy to roll up, easy to share and are there some kind of big overarching themes or trends that you're seeing in the sector the users of your equipment, um, that you can point to?

Simon: 1:05:32

I mean, is it there Like? Is it like you say, uniforms, ecosystems, you starting to see interesting things like the use of AI into your type of tech? Like, where'd you see the kind of the big trends over the next few years?

Nels: 1:05:49

I see we are trending the conversations about AI or, you know, machine learning or or advanced analytics tools. In practice, they're not used very much yet. I think it's early on. You know, people are testing the waters to see what works or see where they can gain value.

Simon: 1:06:09

But you know, as with again all emerging technologies.

Nels: 1:06:14

We'll have a few early adopters, I'm sure that will test these waters. The challenge will be, I think, more on the compliance side. If I'm a professionally trained person giving an opinion and I then decide to put this data into a model that's fit something out, am I put my name on that or not, right, um? And if there's legal liability or compliance liability or what have you, how does that come into place? There's a lot of unanswered questions, I think in the, especially with in regards to how regulatory works with these type of tools, um, but I guess, yeah, we won't be trying them.

Nels: 1:06:58

It just means you gotta. You gotta work through all that yeah, it's interesting.

Simon: 1:07:02

You say that there's nothing like when you've got to put your signature on the bottom of a report to concentrate the mind on whether you're you can really stand over that. It's different if you're using ai to do some marketing inquiry or generate a new graphic or something like for you, but if you've actually that's your, your professional indemnity on the line, it's a different. Kettle of fish yeah, has it?

Nels: 1:07:23

has it made a calculation somewhere that I can't stand over, that's a big yeah a big question, and if something goes wrong, then what happens right is where does the liability fall?

Simon: 1:07:34

so um, back to that word again in my world and the world a lot of my listeners are in is a lot of it is low-cost sensors, back-end black box algorithms, um, generating actionable insight and so on. Um, but from your world, a lot of it is about process-driven monitoring stuff that comes from standards, comes from a particular way of doing stuff, and I just thought it would be interesting just to unpack the differences of those a little bit. You know that when somebody's turning up to a facility to start measuring stuff, when somebody's turning up to a facility to start measuring stuff, they're not just wandering around willy-nilly waving a wand in the air trying to measure stuff. I mean, there's a process behind this.

Nels: 1:08:34

I suppose in either world they're relying on background, they're relying a lot of times on information that has already been gathered prior to arriving on site, whether it's hey, we think we've got someone that was exposed to something here. Or OSHA came in and they found something there we put in this new piece of processing equipment. So this is a change versus last time you were here. Those types of things. So they have, you know, while things can change anywhere in a facility, usually there's some guiding principles to point them in a direction to start, and then they just have their professional experience, and those are meant to sniff things out as well, right?

Simon: 1:09:19

So whereas I think you're right in air quality.

Nels: 1:09:24

Well, where do I stick this in this cube farm out here? I guess I'll put one there and there because there's wall space.

Nels: 1:09:31

You know I think again, this is going to happen with continuous monitoring and hygiene as well. I think, as we have the ability to put more of these things out there, people are going to come up with best practices or worst practices that don't work, and that's going to get shared with the industry and people are going to learn. But again, it's pretty early on in terms of how to use those. In terms of how to use those, and as the models improve as well, how do I triangulate a point source based on placement of these types of pieces of equipment, then that'll help determine better guiding principles, I guess, for application.

Simon: 1:10:12

Yeah, that's interesting. So you think the data data in of itself will help generate some of those processes over time.

Nels: 1:10:21

I do. I think they have to be validated, but it's probably going to be okay. Well, we've put all these out. The data set says probably over here is where our biggest issue is, and then they're going to go do the wand waving and figure out if it's true.

Nels: 1:10:38

But we're going to need do the wand waving and figure out if it's true, right, but we're going to need several you know probably a library of those types of case studies before people will start picking them up as generally accepted principles of how to do studies. Yeah, but today again, we're early in the process, so you'll see them here and there where people have tried new things. A lot of times at the university level they'll do a study of how might we do this type of approach, but it's not generally accepted principles yet.

Simon: 1:11:07

Yeah, and I'm still fascinated to see how we start unpacking this ongoing calibration piece with a better process with low-cost sensors, Because to me it seems a little bit at sea at the moment and we're relying quite a lot on automatic baseline calibration of a lot of these devices and you know some of them have been around long enough where we can rely on it. You know I've got NDIRir sensors here that pretty much on the money. You know I just stuck one outside there this afternoon for a few hours to see if it zeroed back to 400 and it was straight there like it was. It's pretty good, like it's been kicking around my office. You know, like it's abc is pretty good. And but there's others we know much less about. You know particularly PM monitoring that might degrade over time or some of these electrochemical sensors. So how practically we create processes to be able to stand over these devices over time will be really interesting to see.

Nels: 1:12:08

Yeah, yeah, and you know, I think that's a. I kind of skipped over that part of your question, but we know, you know, before you do a study with a dust rack, you should do a check on it and there's an annual calibration recommendation in the factory and all those things, right.

Nels: 1:12:25

So those are kind of known quantities and you know. But with an electrochemical sensor, for instance, if it's in a certain type of environment with high humidity versus low humidity or something like that, the rate of decay could change. So how do you get to that credible data? What are the checking processes that need to be in place so that you can say this is good enough for my application and I've somehow validated that. Yeah, that's Right, yeah, that's all TBD.

Simon: 1:13:00

I think in a lot of cases yeah, I'm just fascinated to see how this crossover or intersection, when we see increasing bleeding from the, from the top end all the way through these tears, where you get this meeting in the middle. That's why I was so interested in the omni track like where that came out of, because it really does seem to sit in this somewhere in the middle between the two. That it's it's high-tech, calibratable gear, but created in a way that's deployable, a bit like low-cost sensors are, in a way that you can walk in with this device and plonk various units around the place and leave them there and, you know, record some data in a kind of a low-cost sense of way. Um, so you obviously saw a market for that in that that there's. There's kind of bleed now between the two sectors.

Nels: 1:13:54

There is, and you know, and again this gets to the uh, you know the 20 question flow chart to try to figure out what your right equipment is right, but the yeah the. The application for that could be. You know what that's going to satisfy the needs that you know this customer has all the time and so they're just going to use Omnitrack and it has the five sensors that they need and they're good to go. But then a different customer set. I'd say, yeah, we're going to use that as our point source location tool.

Nels: 1:14:26

But then once we identify you know, pm is really bad in this- area we're going to put a dust track there, and now we can combine all that data into one location, um, and then you might have another customer that's like well, I only have a. You know, I each consultant here once every two months or once every year. I'm going to buy one of these and have a safety tech use it and guess what. It operates like a smartphone. So it's not a big training hurdle for me, um, for them to get up to speed with it, right? So I think there's multiple different reasons why that that solution came to be in that form factor.

Nels: 1:15:00

Yeah, and then to your, to your point. You know, you could also use it as a almost like a, you know, a low cost sensor network and put 10 of these things in an area and monitor things over time too. So it's very flexible, um, based on a lot of different market needs. We are hearing, uh, but again, meant to be either supplemental or standalone to what other equipment people need, right? So, um, are you seeing some clear use?

Simon: 1:15:28

cases for it boiling to the surface, because, I mean, it did intrigue me. I'd encourage people to go and look at it on the website as well, because it's it is unusual in its in its makeup to try and audibly describe it to people that haven't come across it, it's like a tablet type device that has the the data presented through a nice user interface, but you have this series of modules that you can connect, either on it, although it doesn't exactly connect to it, it just kind of sits on it but you can deploy it, it's just a holder.

Simon: 1:16:03

Just a holder? Yeah, but you can effectively wirelessly deploy this series of modules around a space and they will collect data and present. I could imagine, like you say, a facilities manager that's got quite a big, complex space to monitor, with the right process, could just move these things around in a given organized way and keep track of those spaces, but do it with a device that they can stand over the numbers of because of its calibratability and accuracy and so on. But it's deployable easily enough that it is not going to require a specialist to do it every time.

Nels: 1:16:48

Yeah, I mean those are the main use cases that we've been hearing customers talk to us about. Right, we've either got this you know this area and we're not sure what is going on. So we want to put multiple different types of modules out and measure that whole area in one location. But 10 different parameters, right? So from LHI, co, pm all into one report, which is again part of what makes it easy to use is now all that information is easily imported into a single report and you can compare it side by side instead of having different devices and having to compile it yourself. So that's one of the main use cases. The other one is well, I want to do an assessment of this one risk factor, but I want to have multiple data points done at one time. So instead of coming in with one device for one day over here and then the next day over there, I can do multiple locations at the same location with the same time scale and I can compare those things.

Nels: 1:17:50

So it's really an efficiency play for those people.

Simon: 1:17:54

Yes, that efficiency play again speeding, less time moving sensors around the place and having to reset the report every time, like you, just deploy four or five of these devices around and bang, you get all that data coming in to one device, one report. Yeah, interesting. Yeah, now that's cool.

Nels: 1:18:15

The other part of it, too. That that we've heard on top of that is oh, and, by the way, I'm going to have my safety tech do that and I'm going to be at another site and I can view that on online while it's happening, instead of having to, you know, wait for that that safety tech to compile this information and send it to me, right? So that's the other. Uh, the kind of remote connectivity piece of it is very valuable to some people too, especially with big teams or multi-sites.

Simon: 1:18:40

I was fascinated to ask I don't know if I asked this the last time we spoke, but did TSI see massive uptake and interest in your technology as a result of COVID kind of a false blip, as it were and have you had to go like everybody else had to go through this post covid period of trying to figure out which way up the world is now from a an interested environmental monitoring? Or were you immune to that to some degree because of the types of professionals you were dealing with?

Nels: 1:19:16

No, I would say we definitely felt a change happen during COVID. Yes, and again, we have a diverse portfolio of products, so some interest went up, some went down. It was just depending on what area of the market that was serving. Again, on Port Account, which tests the fit of respirators on a person, obviously that one had a blip right On the aerosol monitoring side, we did see some increased interest on more of the building side and less focus on the exposure side actually, which has kind of reset after the pandemic. Yeah, it was interesting. I think there is a new baseline right. So I think overall it drove the market up in terms of what we want to monitor on an ongoing basis, but obviously we're not up at the pandemic levels in terms of, you know, on the respiratory fit testing side.

Simon: 1:20:21

Yeah, that's a nice way of putting it actually, that you see the baseline shifted up, yes, but it's fallen back from COVID, but the baseline is higher than we were in 2020, kind of thing. Yeah, 2019.

Nels: 1:20:33

Yeah, yeah, interesting, yeah, yeah, interesting, yeah. So you know, we'll yet to see how long that holds, if we hold that or if we see another up or down, but yeah, I think overall it was. I think just good for the industry to get more exposure to what is happening inside of buildings, right?

Simon: 1:20:56

Yeah, no, yeah, I couldn't agree more. Yeah, just hopefully we can continue now I do get the sense we're still and others have said this on the podcast that we're still riding the coattails a little bit of the environmental energy type industry, where air quality in the built environment isn't quite standalone yet, but it's not far off, so it'll be interesting to see where it goes. Nels, look, it's been brilliant chatting to you this afternoon. I really appreciate your time talking me through this sector. I think it's a really interesting sector. I think it's fascinating that occupational hygiene and industrial hygiene is where it's at at the moment. I'd be interested to see how that progresses. And for those that are interested in your technology, I encourage you to check out the website. It's a treasure trove of information, so always worth checking out Now look. Thanks a million for your time. Really appreciate it. Great, great talking to you, simon, really for your time.

Nels: 1:21:55

Really appreciate it. Great, great talking to you, simon. Really appreciate your time as well thank you.

Simon: 1:22:00

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