 For now I'd like to welcome Scott and Shannon to talk to us about scaying up water sensor networks. Thank you. Thanks very much Liz. I'll share my screen. Thanks very much for the invitation to speak in this series it's really exciting for us to reach an audience in the UK and share what we're doing but likewise this is an opportunity for us to learn more about your programs there. We're particularly interested in the digital environment program that's running there and what we can learn from that what lessons we can take away back to the US and moreover we're really excited to work with Liz and others there as we try to assemble a global system for sensor networks. So the thesis that I'm going to share with you today is that there's three parts of scaling up a water sensor network and we'll give you an example of one that went from one in our backyard at the Stroud Water Research Center to one that's now national but has the potential and is starting to creep globally. So, with that as a precursor, I think the first place to start is to explain what Stroud Water Research Center is. We're a nonprofit organization in the United States, we're based outside of Philadelphia, out in the countryside so we're in a very rural area. We have a stream, a high quality, exceptional value stream running through our backyard at the Stroud Center. And so that's given us the opportunity over the last 54 years that we've been in operation to do some do research in a very controlled setting both inside or building and outside so even we have really amazing facilities for doing this both again facilities inside with flow through streams at our greenhouse that you can see in that picture, as well as an experimental watershed where we can manipulate the watershed itself and measure changes and of course a core part of that has long been instrumenting that watershed. So Stroud Water Research Center is also people so we have of course over 50 full time staff, a couple dozen parts, part time staff. And we do three things at the Stroud Center we do freshwater research and that's where we started as a research organization, but we also do environmental education. We have a team that reaches 9000 students per year both in our building and outside our building programs, and a watershed restoration team which works mainly with landowners and farmers to implement better crop management practices. So all of this in pursuit of fresh water. So that's a little bit about who we are where we came from and we've been doing this a while, but you might be asking okay where's the technology coming to play. I'm going to share with you today we're going to talk about two different initiatives that are part of what we call our wiki watershed technology initiative so wiki watershed is an umbrella term that we've created to refer to a variety of mainly digital but also as you'll see actual water and on the ground projects. So the wiki watershed umbrella includes things like a model by watershed, a leaf pack network which you'll see briefly it'll make a cameo into this presentation. Phone apps mobile apps and one, an app for looking at macro invertebrates in great detail so if you get a chance and I'll share the links at the end or maybe Shannon wants to type in the wiki watershed link into the chat right now. So that's all to say that we have we've invested heavily in technology at the Stroud Center, and this is definitely a team effort and the two programs that I'm going to talk to you about today are in viral DIY and monitor my watershed. And so on the right is just a really an abbreviated list of the partners who have contributed to this effort both internally and externally. And it is a team effort and as you know, with your programs. It's a team effort to on many fronts to create and to innovate. And so, that's, that's the way that we will work going forward and we look forward to bringing new partners on board. So we've been doing technology for a while so I thought I'd start give you a little context for when I say while what does that mean. So in 2009 the Stroud Water Research Center had a grant from the National Science Foundation, along with other partners. And it was part of that effort that that really created the need to develop our own data logger. So off the shelf hardware out there. As Shannon's going to explain to you. This was we found the need to do this ourselves. So it was really an in house effort to develop our own data logger that kind of provided the springboard for all these other dominoes to fall into place. And so as we go through time with another grant from the National Science Foundation which created what was the precursor to monitor my watershed which we'll talk about today. The EPA came into play several years later, and they allowed us to build out what became the citizen science program and innovate some of the ways in which we instruct and reach people with our programs and monitor my watershed and and I think that's why I've been pushed even further with significant investments from the William Penn Foundation, which is a charitable philanthropic organization based in Philadelphia. So all of this is to say that we didn't start out with a grand vision. 12 years ago and say we're going to do all these things it was more probably typical of many others where we start, we start in one place we start adding and putting components on to that. And 12 years later, we're at a place that probably a few would have thought that we would be back when we started this effort and Shannon's going to take you back to the origin in just a minute and explain kind of more on the hardware side of things. So our thinking is that there are really when we talk about scaling up sensor networks and creating sensor networks for a community of people. There's really three parts of that there's the people of course and that involves from us, we think about it from not only a scientific research with our collaborators perspective but also from a citizen science, a community science perspective, and bringing technology to people and training them how to use it and in many ways, we're finding successful ways we're learning important lessons along the way about how to do that so there's training they're sharing their supporting a community of people and allowing them to collaborate. There's a platform here and so we're going to talk about some hardware and software platforms, which give people a common interface and these are predominantly open source for hardware and software. But then there's the protocols that we need when we when we think when we move to just thinking about the data itself that we're generating. There are protocols which we need to make that data findable accessible, interoperable and repeatable. And this those fair data practices mean machine to machine communication and spreading a network across different platforms of data sharing. Okay, so with that let's start with the people aspect of saying so this is, we created a program called in viral DIY Shannon was in on the ground floor of this, along with Anthony often camp, a researcher at the Stroud Center who subsequently moved to a private limnotech and we'll mention more about his work in a minute. So in viral DIY was the brainchild of Shannon Anthony and others at the Stroud Center Dave Arscott to create a web based platform where people could join together and share learning and resources. So if you go to in viral DIY.org. There's three main ways that we allow people to interact with each other. By joining the website. There are blogs where people can post feature length pieces we have 60 right now on the website and forums where people can use for q amp a. So I think we have at last kind of like to 2000 q amp a exchanges on there. And we have 700 plus members of environment DIY now so this has become the core where we distribute learning resources to participants and we encourage them to really help each other solve problems of course Shannon and others at the Stroud Center, Sarah Damiano are always waiting in the wings to help people when the community outside can't can't support each other but what we want in an ideal world is that community load lead effort where people are giving an exchanging with one another so that's in viral DIY also a note there that all the material that's on in viral DIY is available under the creative commons attribute attribution share a length license so we're trying to promote open source and creative commons. Perspectives throughout what we're doing. We also have a presence on GitHub. Again in the effort of making our hardware and software open source and build communities people that are using this data. There's extensive documentation on GitHub, and we invite everyone to participate so you can find us there as well. I'm just showing a few of the, the foremost really used and developed repositories there. And of course, from an open source perspective we're using Arduino, and many in our programs are using platform IO as well. Okay, so that's the that's the nutshell of how we bring people together and distribute resources and encourage the community to become over time what we hope is self supporting. We're always there to to develop and refine the resources to distribute, but we're really going after that community perspective. So now let's move and talk about the platforms that we use from a hardware and software standpoint. And one of these is the mayfly data logger. And of course our Arduino being an open source platform as well. These streamline collaboration at this point I'm going to step aside and let our research engineer Shannon Hicks take you through some of the features of the mayfly why why we created it, why it's different and why we rely on it internally and are helping our partners with it extra. So take it away Shannon. So yeah, so I've been working with with researchers for a number of years now to to build really cool hardware to do. To do all the fun electronic collection of data for the scientists so I was tasked with coming up with a station like what you see here in the photo is is what most of our stations look like nowadays. But it didn't start out this way it was kind of a longer process to get to that so when I first started we were going to do the standard approach of using a lot of commercial off the shelf components so next slide Scott. The real stations that we would use would look something like this they're they're $141500 just for a data logger plus some other instrumentation to make it all work together and then you need to add a $500 $600 radio to have some sort of telemetry communication so in a typical package would. By the time you put it in a nice large box with a large solar panel would usually cost around 2000 to 3000 US dollars for one station and that's just for the data logger portion of it and doesn't even count the sensors that go into the water. So when we were tasked with deploying dozens of stations all over just our research watershed. At the Stroud Center, we were going to blow our entire budget just on buying the data loggers, and we would have no money left over for the actual sensors that we're going to go in the water and take the measurement so we could easily look at the budget and say okay well we can't do this the traditional way because we really want a high, high number of stations, but at a lower cost. So, if you look at the next slide, what I decided to come up with is basically building our own data logger and putting in a smaller cheaper enclosure, but which allows us to customize exactly what we need so we don't have to buy something or use stuff that was a little overkill for we needed we could we could target exactly the right sort of hardware that we needed with the right sort of either radios for short distance communication or cellular for longer distance. And we could easily do this for around 150 to 200 to $250 depending on how many features we want to put in there so we could easily cut down the cost of the station equipment by a factor of 10 just for the data loggers alone and that allowed us to then save that money. That we can now spend on sensors instead of just the data logger hardware itself. So it was really exciting for me to take a lot of that knowledge that I've had over the years and try to come up with something and I decided that about that same time when we had a grant to start teaching the workshop to some school people school children and people in like citizen science type programs. So I wanted to leverage some existing programs so we didn't have to do a lot of education of how to how to build a circuit board from scratch or do a lot of stuff that would require an engineering degree or experience with electronics so I decided to use the Arduino platform. Next slide. That if you've not heard about Arduino it's been around for I guess almost 10 years now it's an open source hardware and software program. And this is like a slide from their website and there's lots of great information about it on there, but they, they sell a lot of pre made boards that do a lot of really cool stuff but the nice thing is that they've got software and a great ecosystem of support out there already are books and videos and tutorials. So we didn't have to train people on the platform, we could allow the Arduino community to have that the knowledge base out there so that we could just leverage that when we design a board and a data logger that was going to use that that that platform. So by using that it gave us a springboard into being able to have an easy to use. Platform that non engineers could use it's really great for students and people who are not engineers to use but it's very powerful so that engineers can use it. And there's some really cool tools involved in that on the next slide you'll see what we've turned into for our environment DIY. This is the same sort of idea with the Arduino platform is, we have, we share all of the plans. So the, we've got web pages to talk all about the hardware and the schematics and the board diagrams everything that you need to know for the physical side of thing but then there's also the software side where we share all the sample programs and the code and everything that you need to make one of these things work so it, we've got the whole package there. So we're doing similar to what the Arduino kind of umbrella does with their own boards and software. It's just that our board is specific to what we need to do but we we basically everything that you need to know is is completely open and shared like that. On the next slide you'll see there's a kind of a chronology of some of the boards that we've used we started out with the board on the left which was the Arduino Uno. And if you're familiar with those they basically have these little headers on there where you can plug things in vertically, like an modular kind of side of way of doing things. And the first two there on the left were ones that were our initial, maybe six or eight loggers that we built and I realized at that point that they kind of did what we wanted but I wanted more features and I wanted the better battery life and extra features and so we started using another board called the CDUino Stalker and that had kind of what we needed on there but then I had to build a smaller green board that plugged on top of the commercially available red board to get it to do what we wanted. And that was really great except that about two years into using that the company completely changed their design and change a bunch of features and made it not compatible and so at that point we said well we'd really like to be in charge of our own production and our supply chain so that we can make one of these or 10 of these or thousands of these and know that they're not going to change and that we can build them exactly the way we want. So that's where I came up with the Mayfly Data Logger and basically started from scratch and designed my own board exactly the way we wanted it and put everything that we wanted on there. And on the next slide you'll see some of the different photos that we've had over the years from back to 2013 to 2020. And the first like four versions there I went through very quickly because by the time we put them out a little bit of practice I realized, you know, like the change this add some features whatever but by the time we got to version five and 2015 and 16. Everything was pretty much the same and we were able to to just produce those for the last five years so we've had a really good community and great feedback and really good results with that version. Now on the next slide you'll see. This is the exciting news this is the big reveal here that is the release of the brand new mayfly version 1.0. It's the world premiere of this you guys are the first people to see it I just published it on our website about three hours ago but it's the middle of the night here so nobody over here has seen it yet so this is the first time. I don't know if you've seen it outside of our office that anyone has seen this photo or any of the descriptions of what we're going to talk about right now but this is the brand new board which is, it's got everything that was on the old design, but I added a whole bunch of new features and modernized it and updated it and put some newer chips on then made it more powerful and did a lot of really great revisions over the last like nine to 10 months to get it to where it is now and there's also some new features we've released a brand new cell board because we were having issues with manufacturers, we couldn't even get those the cell boards that we had been using so we're just making our own now we've got a Wi Fi and Bluetooth be we've got a little LCD screen that shows you live data, and a whole bunch of other really great accessories that we're launching today. And on the next slide you'll see there's a great little slide here to show some of the features of the board I won't go through all of them but all this is on our website but you can see this tiny little board that's only, well I've got one right here it's only about, you know, slightly bigger than a than a standard cell phone, actually a little smaller than most bigger phones nowadays. And it's got all these great features on there, and it's completely user programmable using the software that that we share on our website. A lot of questions people say is oh well this is really great I really like this where am I going to get it well, originally we were only planning to make like just a few dozen of them for our own internal use but it turned out to be cheaper to when we got them manufactured to make a whole bunch, and then we thought well gosh what are we going to do with these extra few boards we don't and I thought well why don't we try putting them on the internet. And we've been just super popular from people all over the world do the purchasing so we used to sell them only on Amazon but a few years ago we started up our own little and by our DIY shop page. So on the website there's a link to the shop where you can buy like in quantities of five because it's a lot easier for us to send out five rather than buying large quantities from our Amazon shop. Right now there's the products aren't in either shop right now just because of the release of the new one but they will be here in the next week or so. So, but that's where they are available. The websites are set up to right now only sell things to people in the US or at least North America so the the hits there is there are lots of people who have bought these from various places all over the world using like a mail forwarding system or something like that so I'm sure you guys probably know a way to get us products over there if you if you so desire so we don't have a direct way to sell to people in the in the in Europe or other countries right now. We're still investigating that and trying to come up with ways to easily do that but we are just a water research place for not an international reseller of stuff so it's one of those. I think that may change but for right now, you can get it to Amazon or our shop if you use a method of getting it there using a US based shipping to get it started. But on the next slide you'll see what we can do with the these data loggers is what they work with basically any sensor doesn't have to even be a water sensor but because I work for a water research place. Everything that we use has to do something with water or weather or something like that but there's been people who've used these for all sorts of robots and automation and all sorts of other interesting things, but we mainly use off the shelf commercial research for grade high quality sensors. The benefit there is they're usually calibrated or they at least have some some very good reliability so that you know that the readings you're getting like soil moisture there's carbon dioxide water depth conductivity turbidity the variety of sensors that we use and because we have saved our money on the data logger side we can spend that on those good high quality sensors. And once you know that you've got high quality sensors, then they generate the data it's just the data logger that stores it and then that you know that your data is high quality and can stand up to any sort of analysis in terms of data quality. So on the next slide you'll see a kind of a sample of some of the places that we put those sensors, we put them in farmers fields and on the edge of streams and there's rain gauges we put them in estuary environments and saltwater and and brackish water. We've got weather stations soil moisture sensors down in the ground. Basically, any type of sensor that you can think of can be connected to the mayfly data logger as long as it's as long as you know the protocol and you have the right voltages and you know how the way that you need to get things to communicate to the logger. There's been very few sensors that that we have not been able to interface with. There's been just a couple of random ones that have some sort of proprietary output that a vendor wants you to use their logger with their sensors so they make it really difficult but 99 and a half percent of all the sensors we've ever tried to use connect to the mayfly and we support that in the code and the software that we that we've developed over the years. So on the next slide it shows a little bit about what we what we do with that is I've been building hundreds of these data loggers for our own internal use and we've kind of figured out what works best for us and now we share that with everyone else on the IRDIY website. And then over the years now we've had a lot of requests for us to show people how to do that so we started doing it in person years ago and now with COVID and and all the things going on the last two years we transitioned over to virtual workshop so we can teach a hands on training to people either in person or virtually by providing a list of content kit with everything in there we can either provide the hardware or give you a shopping list and you go out and buy everything that's on the list or something that's very similar to what's on that list if you can't get those exact parts and then we show you how to put it all in a box and waterproof it and then put it out on the stream and put the sensors in the water and then we also tie in the whole database side of things with with the monitor my watershed so you can go from having a box of parts to having a station outside and transmitting data to a website in real time and it's really exciting for people to do that and I think we've taught something like 35 or 40 workshops now in the last couple of years so it's it's been really exciting to kind of fine tune that those workshops and the content and what we've done with that and we've put all of that into a manual that's like 100 and something pages long so all of that is shared online. And we also have videos of those workshops and some other videos and content we put together so that you, you can do a real time workshop with us and we can work with you or you can just download all that material and kind of take the workshop offline by yourself and buy that kit either from our shop or the components and make it yourself and you don't have to do it exactly the way we show here is one of those it's do it yourself it's somewhat of a creative type of thing and we just show what has worked best for us through trial and error but if there's other ways that people want to do things we fully encourage them to to do that and then maybe share those ideas back maybe we'll learn and improve what we've done a lot of things that we've built into this station have come from other people that have shared back hey why don't you do this and we're like that's a wonderful idea so we really love it when we get feedback from the community and everybody kind of builds this together over the years. On the next slide you'll see I did just come another kind of breakdown of all the things that go in there's a data logger that goes in the box and a handful of sensors, and the typical may fly as the older version that's on there, and we put it on a station and then once the stations on the on a pole. The sensors go down in the water, our typical stations are usually connectivity temperature and depth or CTD sensor and a turbidity sensor to tell us about that clarity of the water but we also sometimes add dissolved oxygen or pH or other chemical sensors and to look at the water. And in farmers fields we do things like soil moisture and soil temperature and various sensors that we would use in the ground, and then we also have weather stations in other locations if we need meteorological data and things like that. And on the next slide you'll see kind of what what the end product is is now you've got a station on the stream bank with sensors in the water, and you get some great, you know data we use typically record data at like five minute intervals. This data logger when it's not taking readings is basically asleep so it's asleep 99% of the time it wakes up for a few seconds every like every five minutes and just takes an instantaneous reading and goes back to sleep. And on the small watersheds that we monitor five minute intervals is is what we really need sometimes you could even see get a little bit more than that for a higher resolution for very, very small flashy streams. So if you're doing things like soil moisture and there's a sensor down two or three or four meters in the ground. 15 minutes is plenty for that because the ground temperature doesn't change that often but if you've got a weather sensor, like a rain gauge or maybe rain gauges we do at one minute intervals. But typical stream gauges we record at five minute intervals so now you have this really great data that's stored on the memory card in the in the data logger in the field. The mayfly can typically hold something like it's on an eight megabyte card so it'll hold about 3000 years of five minute data. So you don't have to worry about running out of memory and having to go out and download your logger because it stores way more memory than you'll ever need. And so all that data is stored on the device. What's really nice is if you can transmit that data to a web portal, because you're going to be able to increase your data quality and your response time to things on the next slide you'll see kind of a sample of some of the things we've seen over the years of fouling the sensors get covered with algae and other things in the water or they get kind of fouled up buried in sand, animals with chew on cables sometimes vandals will come along and steal your station. So if flood happens and knocks the data logger in the in the in the into the water, trees and rocks and things will come along and knock things over. So if you've got 300 or 400 stations out like we do we don't have time to visit everyone on a regular basis but if you had all of this data on a website, then you could wake up every morning and look at the map and go, oh this station is offline or this one's data it looks a little, little bad I'm going to go out and clean it. So my vision before years ago even before we could do this was to to be able to put stations online because I had a monitoring project that was about two hours from my house. And there were 400 wells that we were monitoring the water depth on and we had to drive there every week for two years and go out and measure the depth of water in these wells. And the whole time I was thinking, gosh, it would be really great if there was some sort of electronic device that would send this data to some sort of like thing on a computer and this was like almost 20 years ago so all of the technology didn't exist so it's really exciting for me to finally have this dream I had 20 years ago of live data on the internet from low cost homemade devices, collecting real time high resolution scientific data, and it's just been, it's been really nice to see that so the backbone of all of the database and and all of that collection is the mayfly and the technology, but then it's, it's another big heavy project just to have that data side of the, the, the project so that's my portion of the hardware gadgets kind of side of things Scott's going to wrap up now with the third portion of this triangle which is the data side and the protocols that we use for sharing all that data online. Thanks Shannon. And so yeah to round this out. I'm going to talk about that data sharing portal monitor my watershed and it kind of kind of spans between the platform side of things as a way for people to share data, and also addresses the protocol issue of making that data accessible not just on that platform, but across multiple platforms. So as Shannon highlighted the. So the mayfly or choose your data logger choice doesn't have to be a mayfly as long as it can communicate to the web through radio networks or in our case we predominantly use a 4G networks. Now you can send that data to a web portal. And I'm going to give you an example. Today, I'll talk about monitor my watershed for the reasons that it ultimately leads to fair data, but you could send the data to any type of portal that you'd like things speaks another example that some people have used within our community. So monitor my watershed is a, is it a web based data sharing portal that is currently free to use. And it's being hosted currently by limnotech, the company that Anthony often camp has moved to after he left the Stroud Center. And so this is a collaborative effort between the Stroud Center and limnotech. And the, the entire portal is soon to transition over to Amazon Web Services so that we have more flexibility and a better ability to scale that and add new features, etc. So let's just a quick snapshot of what it looks like. Maybe you're already there if you're watching this you've probably already gone there and started poking around. But the first thing you'll find on the browse sites tab is a map of the world with the little pins that show where stations are their color coded to how recently data has come through sites. You can search for sites based on organization on the left. And by site name at the top. There's also you'll notice here I mentioned very early in this presentation leaf pack network. And you'll see that there's a data type on the upper left here by screen for leaf pack so leaf pack network. It's a separate initiative it's under our wiki watershed umbrella of tools. And there's a way to use macro invertebrates to conduct experiments and explore stream water quality. So that's to emphasize that monitor my watershed is I'm going to tell you a little bit more about in a minute is capable of ingesting far more than just time series data. So if you're sharing time series data and you click on one of the pins on the map. The first thing you'll get is a description of the site, and then as I'm showing on the left hand or the right hand side of my screen. Sparkline plots of the last 72 hours worth of data and a description about the site. So it's an easy way to quickly visualize the data from that site and to see what parameters are being measured. You'll notice also in tiny little time series analyst button there on that on the right hand side there so if you click the time series analyst button. You can pull up a data visualization tool that allows you to customize the axes customized parameters are being plotted for one or multiple sites. I picked a random example here from New Zealand. I want to emphasize that we are international there's actually one site in the UK. If you're looking on my watershed right now you're probably seeing that site. So the time series analyst is really helpful for particularly for working with the citizen science groups and Shannon mentioned that along the way that we have in our region we have some environmental nonprofits that are using this tool and bar DIY and monitor my watershed to help them manage their citizen science program so a good tool for lots of purposes. There. So let's let's move and really hone in on the protocol aspect of monitor my watershed and what makes it fair. So, again, we're focused on the open source aspect of this, we're focused on ensuring that ultimately the data that people are sharing on monitor my watershed is being shared in a way where it's findable not just on monitor my watershed, but across what is what is being called in the United States I'm not sure I'd be very curious to know if you've heard the term Internet of water over in the UK. But we're thinking about the Internet of water is this network of hubs and producers and users of water data. So it needs to be findable and accessible. In other words, machine readable so that you can this data crosses different platforms for visualization interoperable, meaning that there are multiple ways to to send data into a database and extract it and then reusable needs to be documented. So how do we make that happen. So, monitor my watershed is a an example of an implementation of the observations data model to observations data model to was designed by some scientists and researchers in the United States. And it provides the the core of the core data service that monitor my watershed provides in terms of a web browser and these functionalities but also the underlying databases that again allow us to ensure that this data is fair in those four ways. So this plot just an example here that just two things to highlight. So the in the mayfly data logger, or in your data logger of choice would be connecting to this monitor my watershed through HDTP post requests to send data into the database and that's being served up on the user interface layer. It's being translated into the database itself so let's talk more about that. So the, the observations data model to is the underlying repository that's managing the data. That data is being exchanged through water one flow for Python with other data hubs for not only sharing data machine to machine but also cataloging metadata. So, there's an acronym on this slide that I'll have to define for you, and it's the consortium of universities for the advancement of hydrologic sciences, that's quasi. It's an academic, academically led initiative within the United States funded by the National Science Foundation and others. In our case we're using kawasis hydrologic information system as the node to which we then share data with the Internet of Water. And again I'd be very curious in our q amp a coming up to to learn if the Internet of Water is a concept and an initiative that's reaching the UK I'm sure you have your own nomenclature for that but it's certainly what we're trying to to build out in the United States. Okay, so that's the quick under the hood of the observations data model to which is being manifest as monitor my watershed. We've had great use and uptake of monitor my watershed. And data records are growing growing quickly so that's again that was really the impetus to move this off of servers into the cloud so that we can manage this data flow more efficiently. We've given you a lot of information we shared a lot of tools we've shared what probably hopefully is a common vision between the need to develop the people side of things platform and the protocol side of things. We have tons of documentation. And if you wanted one place to start. I probably want to go to wiki watershed dot work and go to the help resources and click on monitor, and this will take you to various help resources for all the things that we've talked about today, and allow you to dig deeper into the monitor monitor my watershed aspect of things of three websites to go to there on the screen. And also if you're if you're on the data management and thinking about the database and data management side of things, the underlying observations data model I encourage you to take a look at the frontiers and earth science paper that Jeff Horsberg and colleagues created to share. Not only what the observations data model to is but how it was manifest as monitor my watershed this is all open source anybody can then translate that observations data model to into their own version, their own flavor flavor of monitor my watershed. So this is all open source it's all out there and we're excited to contribute with the community to develop these tools further. So that's all I have and we'll look forward to taking some questions. Fantastic. Thank you, Scott and Shannon. That was a lot of information in a in a really concise package so we really appreciate you sharing all those resources with us and I would certainly encourage everyone to have a poke around on those websites. There, there's so much material on there and it can seem intimidating when you first start but it's all clearly explained so so do have a go with it. I have a few, a few questions. I'm going to start off with, with some from the Q&A box. First one from Mike prior Jones saying thank you for a great talk. Can you give an indication of how much relative effort you put into hardware software documentation and community building work. That's a great question. I don't have, I don't have a clean statistics to throw at that and proportion it out as a, you know, when we think about I can think about it in terms of staff time that are playing roles and all of this. Shannon has masterminded and maintains all the hardware development side of things. And some of the software if you if you go to environment DIY you'll you'll eventually run across a code base that's been developed by another one of our staff. And it's intended to be a data logger agnostic repository of various code that will run these sensors so the idea is make it a little easier for people to do plug and play with a variety of sensors with the logger not just the mayfly. There's another FTE there's another person involved in the software side of things. We all play a role in the documentation clearly Shannon's done a ton of work, most recently to document the hardware and software side of things. The community building when I think about it in terms of effort. This is a much larger effort we have our education department at Stroud Center involved in building out programs really on through different grants to develop workshops to train people. And there are three full time people that are in the community building side of this at Stroud Center so maybe in terms of effort, maybe if the general answer would be we probably spend more time with the community building and outreach side of this. Anything else that might be a short answer. Thank you. I have a question from Beatrix LaBritley and who says thank you for an excellent talk. Could you tell us what temperature range the mayfly has been tested at so far. Well the mayfly board itself that uses industrial range electrical components so there's no, there's no problem there in terms of temperature we've had. It's one of the minus 10 minus 15 minus 20 C a few times. At that point it's more of the lithium battery that powers them doesn't really like to be that cold, especially you're not supposed to even charge a lithium battery if it's below freezing so around here usually when the warms up there in the daytime the sun comes out it kind of does a little bit better but it's usually the battery that's a bigger issue, or the fact that we've got sensors in water and when it's that cold the sensors in the ice freezes and things get damaged so the mayfly itself is very very hardy I've had some that have been out for five or six years, and are still working fine. The only thing that kills them is moisture if there's a leak in the box or some sort of condensation happens inside the box, then the circuit boards don't like it when they get wet. And in the summertime, an enclosed opaque box in the sunshine will get up to 40 or 50 degrees Celsius in there so it's like a little miniature greenhouse. And again that heats up the circuit board, but it's not a problem I've actually tested the mayfly when in development by putting it in my freezer and putting it in my toaster and doing extremes with it. And again, the board doesn't doesn't mind it but you really don't want to overheat a lithium battery because they tend to burst into flames so it's more of the battery or the sensors that are going to be the temperature extreme problems for you because otherwise the circuit, the circuitry can handle a really really extreme conditions. Thank you Shannon. I'm glad to hear I'm not the only one with science experiments in my home freezer. So a question from Oliver Tills, who also says brilliant talk. Thank you. They grew para an earlier stage in the development of approaches for measuring biological responses of early stage aquatic animals alongside environmental data, which is tied to a web based interface. Do you work with cameras or video and integrating this into your other systems. I don't know that we've done any type of work with video. But in that context, we do have community science programs that Shannon's interfacing with that you video build time video on their rivers, where they're measuring data to visualize changes but match what is happening in the stream with the sensor measurements they're making. Shannon, do you have any follow on to that. Yeah, no I mean I think with that back actually years ago it was it was easier to just have a camera, like a time lapse camera taking a video or a photo of a of a stream rising 15 or 20 years ago, because my personal electronics were a lot different back then so I actually, some of my first environmental monitoring equipment was a homemade camera time lapse thing to use to monitor floods like that. But there are much cheaper and easier ways to do that but yeah because we've used the sensors that we've got nowadays we haven't had a need for that but I know there are a few folks out there who are using that. And there's there's especially with new with computer image processing and stuff you can do some really amazing science with cameras and and video work but we don't have an easy way to interface that with monitor my watershed just yet and we don't use in our research but I know people who are using that. Thank you. Question from from Matt Fry. And what are the key considerations you've had to make or lesson learns when it comes to making this sort of initiative as self sustaining as possible. So from self sustaining I'm going to interpret that is from the perspective of our environment DIY community that we're trying to build on the web. And what we're, what we're ultimately shooting for is, yeah that kind of grassroots support from community to not only share with answer other people's questions, and we're getting there. And it's really exciting. Now with 700 plus people interact that website it's exciting to see how much people are giving and supporting each other answering questions. In terms of Shannon might have some add on to this, but I would say one of the things that we worked really hard at is to extensive resources and documentation. We have videos of how to use. We have manuals that we've interactive manuals do every step along the chain from, you know how to install Arduino and and for for beginners, all the way. That's what we think of as more advanced troubleshooting and how to deal with your data in a troubleshooting fashion. So I think that my key answer would be to make the resources available and to make sure they're easy for people to find and use Shannon any follow No, I think you said that says that's the whole point of environment DIY that's the why and DIY stands for yourself because we want people to be able to do this and we just want to provide them with the hardware and the tools and the software and you know platform to use it on but they need that information of how to put it all together and how to maintain the station and how to once they put it out there how are they going to keep it running for years and collect that they the data that they need so to make it self sustaining is that the last portion of everything that we do is to make sure that the end user is able to continue and find the resources that they need so we put a lot of effort into all of that support network so that once someone does have one of these instruments that they have all the tools that they need so that they can ask us or other people on the in the community to for any of that help and that that's been a real, it's been so exciting to see the, I think that the chart of users that we've had on the website looks similar to that that upward curving line of data, it's exciting every time I log on to see more and more people are joining and other people are answering questions and we're just building that that community and that support network so it's been really exciting to see it grow over the years and I'm excited to see where it's going to go next. Thank you. A question that I have, which is a sort of slightly slightly more operational academic one, have you, how have you found getting the project funded because a project like this relies on having long term funding for for personnel to to continue doing it and science agencies are not always so keen on programs with monitoring in the title, you know they want new stuff. How have you found getting it funded. I'm pretty good at persistence and exploring all the resources we've been very important to have some in our world, a three, a three year or five year NSF grant is a long grant, perhaps that's similar there so these initiatives really started out as longer term three to five year grants that we're able to really make headway, and there's been lots of work creative, find ways to make this project and these products relevant to programs other initiatives and other communities. It's an important part of finding the resources where you can. And that means making it relevant, and finding outcomes that people can achieve with this to take it in their own direction of course it helps that we really promote the open source side of things and this is free for anyone to take it in their own direction so I think that's another helpful part of being flexible and make sure that you're thinking about the outcomes for the stakeholders for the communities that you're working in. Thank you. And then a final question from Steven Hallett are on our panel and to two questions really about remote access to the data loggers and first, have you considered developing the board. So you can update the firmware for example from a central location so you don't have to go out to the systems to do any updating. And second, is there a way of doing adaptive monitoring frequency for example if there's an event that you see can it trigger increase sampling and then go back down again. Can you do that remotely or do you have to visit the site what what the options for. Those are great questions we've, we've, we've tackled those issues both over the years, the remote programming, it can be done we don't typically do it because we have to visit our stations, fairly regularly to clean them, because it's a sensor in the water and so we've got to go out there, or, or the data is not going to be good quality so we're going to be visiting it anyway so it's just as easy to just program it then, then to build the technology and to to program it. There are a lot of data loggers and locations but there are no radio coverage. There's no cell phone or Wi Fi or anything. And there's, it's just like, actually in this photo that's my background is up in the Catskills of Southern and there's there's no cell phones or anything anywhere and you got a hike a couple of miles into the woods to visit a station so stations like that the only way to get to it and update it is in person. But there are cases where you could do an adaptive sampling where you could take more frequent data than than than is necessary if, especially if it was a station like is on the edge of a farmer's field and doesn't see very much rain but maybe a big rainfall and you want to take super frequent readings but most of the time it's completely dry and you don't need to be sampling a dry field with no water in it. So in those cases yeah we've done that where if it detects water or change of a certain rate, then the sampling rate increases but then when it goes back to another slower rate after that event. We've done the same thing using rain gauges or pumps that sample water based on when water gets to a certain depth, it will actually trigger relays that will turn on water pumps to sample water and do things like that so. Yeah you can make it as smart as you want because you have full control over what the circuitry does and you can add any sort of circuitry to it. The vertical station that we normally use just takes data every five minutes for standard stream measurements, but we do one minute increments I've got it I had a data log that was taking one second increment readings and filling up lots of data really quickly but it just, it really depends on what you're what you're sampling but that's the that's the benefit of having full control over the hardware and the software is that you can do whatever you want if you buy a manufacturer's product and sometimes you can only choose from a drop down there's a certain number of choices of something and you can only use sensors from that one manufacturer and with ours you can hook up any sort of sensor and make it do whatever you want and that that's been really nice to have the the flexibility and the the ability to work with just about anything that we've ever tried to do. Thank you very much.