5 min reading

17 May 2022

17 May 2022

TEK-Talks with Thingy IoT. Forecasting forest fire activity with LoRaWAN®

TEK-Talks with Thingy IoT. Forecasting forest fire activity with LoRaWAN®
TEK-Talks with Thingy IoT. Forecasting forest fire activity with LoRaWAN®

Barney: Welcome, everybody, to our new series, TEK Talks by TEK Telecommunications. For those of you who don’t know me, my name is Barney Barnowski, and I will be your host. Here, with us today is Scott Waller from Thingy IoT. Thingy IoT has developed a unique solution to address forest fires and help reduce the massive impact that they have on our ecosystem, human lives, and obviously the economy. We all know global warming is a significant contributor to the increased number and intensity of forest fires, and we urgently need means to forecast fire activity before they become too large to contain. So, on that note, you may have picked up on this by now…our topic for today is forecasting forest fire activity with LoRaWAN® and with Scott Waller from Thingy IoT.

So, Scott, thank you for coming, and please introduce yourself and give us a quick overview of your solution to those out there that are not aware of Thingy IoT. 

Scott: Well, thanks Barney, thanks TEKTELIC. Yeah. So, as you mentioned, Scott Waller, CEO, and co-founder of Thingy IoT. We started this endeavor several years ago after a tech challenge from the Environmental Protection Agency here in the United States around developing a lower-cost sensor, specifically around the output of wildfires, whether it’s firefighter safety and exposure on the fire ground or the public at large as the smoke moves from the fire scene and into the public areas. And, you know, and specifically, LoRaWAN®, was the LoRa and LoRaWAN® was our initial connectivity option for that, and we continue that today, just extending into a very remote environment. And so and beyond that Thingy is becoming an integrator of LoRaWAN® and enhances our deep partnership with TEKTELIC as well as an operator in LoRaWAN® networks all throughout the west of the United States.

Barney: Fantastic. So, let’s shift gears a little bit for a second and maybe get a little bit more technical.

So, from a technical perspective, can you give us an overview of how your solution works and specifically how it addresses the forest fire issue?

Scott: Yeah. So, you know, one of the things in fires is obviously it sends up a plume of smoke and those are byproducts of combustion. Those are particles, particulates, carbon particles, methyl apple, bad stuff we might call, you know, especially when they get into urban environments, you know, the plastics and all that are burning in the air. But they also send up an immense amount of gases in different forms carbon monoxide, carbon dioxide, volatile organics, and other gases specific to the fires. And so one of the challenges from the TEK challenge itself and what we’ve seen over the past few years is the sensors that are out there, especially in rural environments, to measure air quality and inform the public. Is it healthy to go outside or stay inside? You’re way too expensive, very regulatory, very scientific, very exact tens of thousand dollars, sometimes in the $100,000 range. And so there is a need for a lower-cost solution, but still high-quality data. And so as a part of that challenge, what we’ve done ever since then has partnered with the different agencies to bring a lower-cost solution down with off-the-shelf chemical sensors and particulate sensors, but with a high degree of integration of all those sensors together, calibrate them off the shelf at the factory and do our own work and then spend a ton of time other research firms and the regulatory agencies to validate against the standard, the high-cost standard in the hope, in the end, is to be able to get more and more sensors in a diverse area so we get more data points that bring that data closer to home.

Barney: Right on, right on. And I imagine by reducing the cost of the endpoints themselves, you’re actually able to capture much more data. Right, which is also programable.

Scott: Correct. So the forecasting area, so you might see smoke events during wildfire events. Right. There’s the weather forecasting side that’s very critical to the operations of battling the fires. At the same time, on the smoke side the agencies are looking at, well, how can I give a better forecast of when the smoke is going to be bad in your area? Is it going to get better today or is going to get worse? Most of it is just weather work and not everyone trusts the weather. So by putting a more diverse set of sensors and more regions in more areas, especially because of the topography and the diverse nature of our weather patterns, especially in certain areas, then it just gives them more data points. That increases the forecast model. So we get better data in the end.

Barney: So we understand that when you were designing your solution, you looked at a number of different IoT technologies.

So what made you decide to proceed with LoRaWAN®?

Scott: The one part is most of these areas we’re going into are very rural. Connectivity is limited or poor, so cellular is not guaranteed. The satellite is still way too expensive. We’re starting to get more options. We’re not talking, you know, the high bandwidth broadband solutions by some satellite providers these days. We’re talking IoT-based solutions. You have to keep the cost down overall. And the cost is also relatable to the power aspects of cellular radio takes more battery power because it draws more power in general. LoRaWAN® seemed to be a really perfect solution for both long-range connecting lots of centers at a very low cost, both the power rate, battery power usage, as well as the cost of overall service. And one of the things is in some of these very remote areas, you might have cellular on top of a mountain. So we can put a gateway up there and extend the coverage into a valley or a very large region down below where there is no cell coverage to connect our sensors and get that data connected to in the end into the Internet so we can do analytics on it.

Barney: Right on, right on. And I mean, just from personal experience, right? We’re no strangers to forest fires here in western Canada and Alberta in particular.

So if we were to say convince the powers that be here to take on your solution, how simple is it to deploy and operate your solution?

Scott: Yeah, definitely. So the first of all, first and foremost, you know, kind of mantra was keep it firefighter simple. You know, you’re out in the middle of a risky situation. It’s, you know, high adrenaline, get it out there. And whether that’s a firefighter or a researcher, you want to get it up there in a very extreme situation. So for that use case, it’s a tripod, pull it out of an apocalyptic case, drop a tripod bolted in and push one button, turn it on. You could set up a remote telemetry unit. Again, we’ve packaged more gateways into very remote hard cases that we can put out there at the fire scene. Make that super bulletproof. Right. It’s going to be introduced to extreme conditions. The others are more regulatory. So you think about your air quality management district or your weather network or maybe some researchers where they’re permanent. We’re going to put them out there, run them off of power or solar power, whatever, whatever is available in the area, and connect them either LoRaWAN® network or extend a lot of a network out to those. But those are permanent installations for long-term studies of what it is.

And then the other is in some of these areas like agriculture, where we’re putting out these and a ton of different vineyards is a part of a USDA Department of Agriculture Research study around smoking wine grapes. So, you know, we’re putting them at the site of the vineyard or tying them to a trellis pole. And so those are either short-term duration or long-term duration studies. So, we try to be super flexible on both the power, how you connect them, and where you place them. But in the end, we want to get really good quality data and keep it as simple as possible for both deployments as well as usability.

Barney: Yeah, no, that’s fantastic, right? And certainly, got to protect those grapes.

So what’s the feedback been like? What are your customers saying about your solution? 

Scott: You know, so we’re constantly evolving it based on some of the projects that we get involved in. Well, you know, the one target is obviously the regulatory agencies, and there are some defined standards. And can we meet those standards with a high degree of accuracy and that we’ve proven over the last couple of years, again, in close partnership with those agencies against the highest standards in the world of air quality measurement. And we’re constantly improving that and taking that feedback and correct algorithms and correct software and correct features and add new features specifically for that user group.

On the other side, a lot of the research grants we’re working with, some of these universities, whether it’s agriculture and smoke taint and wine grapes, or that’s worker safety workers that are out there picking the grapes or fruit during wildfire season or a smoke event, as we call them. They need a wide net to test, to figure out, well, we don’t know exactly what’s happening, but if we get a large data set of all of these chemicals that are being exposed either to the humans or the grapes, then we can take that and correlated with their research work in the back in the lab and really try to identify can we get a, you know, the ability to early detect some of these things that are harmful to either the humans or the crop, whatever it may be. But it’s that wide net that gives them the flexibility that they like in hopes that, well, we don’t need seven chemicals, maybe we only need one or two, and so we can remove those. And we made it super fungible.

Barney: Okay, fantastic. So earlier you mentioned that at least in the portable use case, you actually package our gateway with your complete solution. So maybe you can talk a little bit about that. Maybe just a couple of minutes.

What made you pick the TEKTELIC gateway right, specifically the KONA enterprise? 

What specifically due to you, to the TEKTELIC solution, obviously in TEKTELIC itself?

Scott: Yeah, on the gateway side, it was super excited when the KONA enterprise came out. We’ve been working with the Micro and the Macros for quite some time. But in these really remote locations, its cost, its power footprint, and then we really don’t need 64 channels. It’s not an urban environment, there’s a lot of noise. I mean you might want to sell 64 channels out there.

Barney: You might. One day, you might.

Scott: But we have that portfolio and the behavior and configuration just work from platform to platform, where they are running. We know it, we trusted and so that enterprise was the perfect mix. We needed 8 channels. We can do external antennas. We’ve got a great LoRaWAN® antenna. We use the high gate antennas from you guys. We have the power of the solar solution. So solar panels, batteries, charge controllers and then having both broadband and LTE connectivity as a backhaul. It’s the right mix of cost and power for these because instead of putting them on a big tower and covering a very, very large area, we might be putting them on the side of a barn every few miles. And it’s just that, that right mix of power and cost and further use case which is connected to a bunch of sensors. We’re not connecting hundreds of censors inside of a city. So it’s a different use case and it was the perfect mix.

Barney: Absolutely. Well, Scott, thank you for that great feedback. We totally appreciate the customer feedback. It is obviously very important to us as we build and innovate on these things.

So, Scott, what does 2022 look like for you then? What is coming up in the new year for you? Do you have any new deployment opportunities? 

Scott: One of them is that the number one focus over the next month as we get into what we call fire season. But now it might be not just a season; it’s all year long, unfortunately around the world. But there’s a big focus, obviously, on hitting that season down the entire West Coast of the United States in these agriculture and rural regions, for a bunch of different research studies, one of them being one of the largest US Department of Agriculture studies with multiple universities and ourself on characterizing smoke, as you know, being exposed to wine grapes across the different wine-producing regions, multi-billion dollar industry. There’s a lot of loss and so we want to help further that research.

But at the same time, we’re working with some of the fire agencies on how can we use this for a predictive response? Because the network is a platform for things like fire weather modeling and some other work where we’re providing additional censors from the ecosystem as a part of this data collection strategy. And what was of networks in some areas in Washington state there’s not going to be, you know, hundreds of networks down the coast of which that becomes again the platform where we can add other research projects, in one of them being some public health exposure work and then some worker exposure. Worse, there are new rules and regulations around what you can be exposed to from the kind of worker exposure and the insurance perspective.

Barney: Yeah, but just going back to that statement you made about kind of the wine yards, though, it sounds like you’re almost doing the correlation study between vintage and how the smoke affects the different vintages. Right, I mean, can you talk a little bit about that?

Scott: I mean yes.

Barney: Your safety is absolutely critical, right?

Scott: So it’s not just about that…no one can truly say. Well, if I detect smoke in a certain type, then we know exactly what the output is going to be after the wines have been fermented and put in a barrel roll, aged for over a period of time. Right, chemistry changes during that for maintaining process. So what we’re really trying to do is a kind of back to that net strategy. Let’s look at where the smoke is moving through these regions, how it ages, and how the chemistry of it changes, and then correlate what we’re measuring at different stages of the grape growth factory. Actually, there are some studies in all three states, Washington, Oregon, and California, forward we’re replicating. Throughout the summer we’re actually generating smoke in certain areas, in very confined environments or controlled environments, and it will measure that through the different stages of grape growth. It’s about ready to pick and with that exposure and correlating, what is the chemistry output after fermentation. That’s what they’re trying to draw the line in. And how can we eventually predict what is that type of exposure and then what is the output? So then they can create mitigating effects that are part of it. Do I wash them? Do I.. What is my treatment? So there’s a lot of this work of about 40 different researchers and we’re providing some of that modeling data and the sensory data, along with weather data. We can just add to that data, so eventually have some really cool output for the whole industry.

Barney: Yeah, this is absolutely fascinating. I’ll be entirely honest with you, right, I mean just being able to sort of make those correlations and pull in that data to be able to sort of effect. Literally, at the end of the day, you’re helping them modify the recipe if they need to.

Scott: It’s not just wine grapes, it’s not their crops that we are starting to see as well. Because you know that the is the smoke is going to be up there, it’s going to constantly be evolved. We can’t pinpoint where it’s at. So the larger we have a distribution of sensors in this industry, it’s affecting other industries as well, and so hopefully it advances the research. We can continue to provide just a network as a platform to be able to do more and more of this.

Barney: Phenomenal. So, Scott, the last time we met was, I think, at IoT World and we both saw lots of different solutions. Some of those solutions, TEKTELIC’s developing were focused very much on real estate, industrial, acid tracking, and even more recently we’re very focused on e-health, so medical wearable devices.

So with so many different IoT vertical markets and different use cases that are currently wiring on LoRa, in your opinion, what do you think or what do you predict will be the highest adoption use cases of IoT in the coming years? And obviously why?

Scott: Yeah, so I mean we’ve obviously talked about some of the agriculture stuff, the weather stuff. You know the soil moisture sensor has been great. We’ve been using your gas platform for a while. Get those out in the field, because if I can add additional measurements on what the soil moisture is doing about the health of the wines and the crops, et cetera, really adds again to the data that we’re gathering. Acid tracking becoming a really big thing, not only in the agriculture industry but, and you know, if we’re building a network in these areas for the agriculture industry and you know, we’re doing microclimate measurements and smoke motoring and stuff like that in vineyards and orchards and, etc. They want to know where their truck is, and when it leads after the packhouses and distribution centers. Can we do some type of linkage? Can you give us small bits of data? Since we have a lot of LoRaWAN® networks in these regions now, can you give me data on when that truck is arriving? Three minutes so I can have a forklift ready and just optimize that supply chain. So tying that stuff together, you mention other things like you know there’s you know we got cold storage monitoring and stuff like that because that’s really tied into that industry. If they lose their coolers and chillers in some of these areas and they can lose a really big crop that’s in cold storage.

And then the other one, you mentioned the eHealth solutions right there was the application kind of in those COVID days, but I’ve been having conversations with some of the research folks that I’m working around. You know we start talking about workers’ safety out in the field. It’s posed to smoke, but it’s also, you know, 100 degrees far out front out there when they’re picking things, so use that may be as a solution to monitor that side of it. Then also, you know, as a previous firefighter myself, I’m really concerned about the health of the firefighters that are out on the line, and so we’re having discussions with a bunch of different groups around. Not only were going to provide the smoke data and maybe the environmental exposure data in general, the weather. How much heat? But could we use those types of platforms as well to further research but keep it as non-evasive as possible? Because the last thing the firefighter wants to see, you know a 10-pound pack with a bunch of sensors on it. They want to superimpose. Can we use those solutions? There, are a lot of new ideas for just that ecosystem, what you guys have in your portfolio and the whole LoRaWAN® ecosystem. It’s great because there are a lot of options.

Barney: Fantastic. Well, Scott, listen, thank you so much for spending the time with me this afternoon. You are truly an IoT environmental pioneer, so I really enjoyed this chat. So again, thank you for making the time. Thank you for being a TEKTELIC customer and we’re really looking forward to seeing what 2022 and 2023 bring for the best name IoT company in the IoT space ever by the way. So, you’ll have to tell me about maybe on another podcast how he came up with that.

Scott: I appreciate it Barney and the TEKTELIC team, the entire team, David and sales, and all of it to Roman. So thank you guys for the support. You guys are a great partnership.

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