Transcript 0:00 Talk to me. Information, news and entertainment on demand. WUSradio.com. 0:10 [on hold music] Welcome to The Peggy Smedley Show, the voice of IoT in our connected world, with your host, Peggy Smedley. Hello, listeners, and welcome back to The Peggy Smedley Show. 0:26 As a regular on the show, my final guest needs no introduction. As an assistant professor of agriculture and biosystems engineering, he joins us this month to talk about his thoughts on edge, cloud, fog, and even mist. 0:39 Please welcome Joshua Peschel, Assistant Professor of Agriculture and Biosystems Engineering at Iowa State University. Josh, welcome. Peggy, it's good to talk with you again today on this very snowy day in central Iowa. 0:55 Uh, why? I thought spring was coming, Josh. I think you need to do like a dance or- Uh, we thought that, too. It was nice and sunny, and now we got all this weather. 1:02 But it's, it's pretty relevant to, I think, what we're talking about today, so it's a, it's a good kickoff. Well, then you'll have to start. 1:09 I need your input now on what's going on and, you know, all this smart agriculture, how we're gonna use it with the cloud and fog. You're educating me. 1:19 I had to do the due diligence of checking out mist 'cause you're bringing some new knowledge to me today. 1:23 [laughs] Well, some of it is how, how people talk about things, and so I'll, I'll, I'll just run through those three things that you mentioned really quickly. 1:31 We'll get to the mist a little bit later, but I wanna share with you, I think, where I'm coming from on, on how we define these types of systems and then some specific a-applications in smart agriculture. 1:43 So just really quick, the way I look at this is, you know, in cloud computing, we've got, um, all of our information, all of our data that we're collecting from all of our Internet of Thing devices, and we're transporting them, or putting them back up on a physical server somewhere. 1:58 Okay? So it's not all that different than what we've done historically, it's just access to them is a little bit more, more easily. 2:03 And so we're putting them there for the long term, and we're doing our analysis, and I think that's the most important thing to talk about there, uh, on the server. 2:11 Some really good examples in agriculture when we come to, uh, cloud computing are the directions the remote sensing has gone to, uh, specifically all those, uh, drones, those small flying robots that go out and collect massive amounts of imagery from, uh, agricultural fields to try to estimate moisture content, crop yields, all those kinds of things. 2:34 No longer are we sending that information back to our desktop through sneakernet. 2:39 We're actually pushing all of that through to the cloud, and companies have spun up to actually do a lot of that processing for us on the back end and give us what we're interested in, which is yield data and some of the, the meaningful results. 2:52 So that's how cloud's coming into, uh, smart agriculture. So fog, fog gets us get-- kinda down to the next level, where we have, um, more of a distribution on a local network. 3:04 The information is being processed out on, let's say, uh, sensor nodes or some, some gateway. I think a, a good example of that might be like in wireless irrigation networks that we see popping up. 3:14 And so you have these little sensor nodes that might be detecting how much moisture's in a particular place, but they're kind of all talking back to a central controller that maybe is at the pump that will route water to areas that might need it most. 3:27 And you could also say that might be true about, um, putting nutrients out in locations and things like that. Now, some people talk about fog and edge as kind of the same thing. 3:37 Edge gets us out to pushing the processing and analysis and the data storage way kind of more towards the edge of where that network is at on the individual nodes. 3:47 And so I think a good example that I would describe edge computing being is what we do kind of at the cutting edge of mobile rapid phenotyping. 3:56 So that's sending those small little shoebox-sized robots into soybean fields and sorghum fields where a lot of c-- data is being collected on board, 4:05 processed, stored, all that, but it's sending back kind of the equivalent of text messages or tweets with regard to the information of interest at each individual plant, or maybe it's looking at livestock instead, or each individual animal. 4:21 And, um, and that's a, that's a kind of more of a future direction where autonomous algorithms are being developed and different ways to, um, you know, maximize that type of data collection. 4:33 So that's how I'd kind of break out cloud and fog and edge as it relates to smart agriculture. 4:40 So, so if I get you correctly, you want the edge to be right out in the field, so to speak, right on those animals, the, the agriculture, you know, things that are happening as close to the action, so to speak, as possible. 4:56 Absolutely. Put it out there as far as you can, and, and there, there are some real positive consequences to doing that. 5:04 So I was just asking if you wanted to talk about the, the mist now as we push forward out into- Yes, I do because-- Yeah. Yeah. Absolutely talk about mist. Perfect. 5:12 So mist you can think about as giving us strength in numbers, and mist really takes it out to about as far as you can possibly go, gives us really lightweight and various rudimentary ways of sensing. 5:24 But the win is, is that you can, you can deal with a lot of these low data rates. You can deal with, uh, low power consumption needs. 5:34 Um, it's really great for lofty networks, where if you think about it, if some of these nodes drop off, they have to self-heal. 5:42 They need to go back to, you know, collect data, send it at a later point, and that's really, really important for perhaps not only agricultural systems. But let's say we wanna go up into Alaska. 5:53 We wanna study, uh, climate dynamics, stuff in the tundra. Uh, we're really far out there. We might not have a lot of power. We might not be able to push a lot of bandwidth. 6:03 We can't go there and deal with it, so as much as we possibly can, and you-- that's why you kind of talk about it in the context of mist. 6:10 So you have these really, really small independent particles, um-That, that can send information back ultimately to what we kind of categorize as the, the fog level. Okay? 6:22 It might not necessarily, that information might not trickle back up to the cloud, 6:26 um, but m- it's mostly there to push it as far as it can go with the minimum power, minimum bandwidth to inform that fog level and, um, and that's the direction I think where we're going with the mist computing. 6:40 And, and I'd say that that's the newest of all of those technologies. It kind of reminds me of what mesh used to be. Like, you know, when you would throw those out and you would say a mesh network, really wide area. 6:52 Is that kind of in the same area, kind of description what you might w- say mist is, has that same familiarity to it? It is, but I think it's more independence on the individual nodes. 7:04 So I think the architecture's not all that different, but I think the independence and the reliance on the local localized computation is much, much more heavily. 7:12 So if you think of all these nodes as, you know, I guess in theory, uh, c- could be, you know, completely autonomous agents in themselves, um, some, at some point in the future, um, 7:25 they don't necessarily have a dependency on the network, but they're able to provide information back to it. We've only got about a minute and a half. 7:34 Looking at this, how are we seeing, you know, let's say academic, you know, academia or business and, and regulatory, you know, starting to support all of these cloud-based solutions, I guess, you know, the future of ag or any of this that you've just described. 7:50 Where are we headed with all of this? So I think we're doing a really good job in the teaching space. 7:55 Certainly we've got classes on IoT and wireless networks and low power electronics, all those kinds of things, so we're pushing forward the ideas and the technology. 8:05 Business is making those technologies available to everybody, taking them from the laboratory to the field and putting them in the hands of everyday people who can gather this information. 8:15 I think it's being encouraged by the government because there are funding programs from DOD and DOE and NSF and all those to support both of those initiatives. 8:24 I think in the regulatory space, IEEE, for example, does a good job, but my, my kind of the personal opinion that I'll end on here is I think while there's so much innovation, so much technology coming out, we're getting so much, it's starting to look like a big mixed fruit salad in, in, in terms of this technology with this protocol, can it talk to this thing? 8:44 And this new one, can it talk to that? And how well do they work together? 8:48 We really need a real strong effort towards a good taxonomic classification of what's out there, of the technology and the protocol, and make sure that as we move into the future, that, uh, the interoperability of these devices, so to carry over a theme from last month, isn't a problem for us. 9:06 Hey, Josh, I love when you're on the show. Thank you so much for being with us, and I look forward to seeing you April sixteenth at our Skill Set Academy. Absolutely. Good to be with you today. 9:17 All right, listeners, we're out of time. Remember, we are broadcast live every Tuesday at twelve PM Central. As always, this is The Peggy Smedley Show, the podcasting voice of IoT and relevant technology. 9:28 And remember, with great technology comes great responsibility. Have an awesome week. 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