 It's one o'clock on a Monday afternoon, so you must be watching Think Tech Hawaii, Research in Manoa. I'm your host, Pete McGinnis-Marc, and every week we bring you research experiences from the Institute of Geophysics and Planetology at your H-Manoa. Sometimes it's geophysics, sometimes it's planetology. And boy, we've got an exciting show for you today and a slight variation. We have a guest who's a remote location. So I'm very pleased today to introduce Dr. Milton Garces, who is a researcher within the Hawaii Institute of Geophysics and Planetology, but Milton has his lab on the Big Island. So he's joining us live via scope. So welcome, Milton. Hopefully the weather over on the Big Island is just as good as it is here at Manoa. And you're talking about something really exciting as far as I can tell. You're going to tell us about infrasound. So tell us a little bit about infrasound. What is it? Hi, Pete. Well, good to be here again, kind of building on a previous presentation, kind of escalating the level of detail that we can do with the tool that everybody has at hand. We're learning how to collect geophysical data, scientific data with cell phones. And to understand how we got here, I'm going to rewind back to some of the natural sources of very deep sound, which is infrasound. Infrasound is sound that is generally below the hearing threshold of humans. However, it's been there from the beginning of time. And it's also there, it's from the moment of our conception, the heartbeat of our mother, the breathing, the respiration. There are all these long period cycles that are part and parcel of our daily life that create sound and the we call infrasound. So the audience has probably become quite familiar with the idea of looking at different wavelengths of light into the infrared or the ultraviolet. What we're talking about is the audio equivalent, wherein we're hearing frequencies which our ears aren't susceptible to. And unlike an old person like myself who loses his high frequency hearing as he gets older, infrasound, which you study, is a longer wavelength. So it's a lower frequency than what we can actually hear. Yes, it's a deep vibration. And at a certain point in pitch and frequency, we lose our sense of tonality. And what sounds like a long period of tones, they're something like a beach. And well below that, it turns into a sensation. If something is loud enough and deep enough, you feel a physical displacement of the movement. And so even though we are sensitive to very low frequency sound or infrasound, we sense it differently. OK, and so there's a whole spectrum of frequencies. You can presumably study different phenomena. You're sort of a physicist, a geologist, an engineer. So can you tell us a little bit about which kinds of phenomena you can study using infrasound? All right, so we're going to put our infrasound goggles on. So like you pointed out, it's equivalent to all of us and we can see into the infrared. So let's pretend we can hear into the infrasound. And some of the sources that we have, I don't know if you have that slide up. Yes, if we have the first slide, I think. Here we go. And for the listening audience, we've got somebody on a large wave surfing. We have in the middle top something, I think, related to tsunamis. Top right is an air burst, probably for a media coming into the atmosphere. And then down at the bottom left is a volcanic eruption plume. Bottom right is a hurricane. So you can study all of those phenomena with infrasound. Yes, and so I'm starting on the left side with that. That is the chopper, which everybody knows to listen. There's extreme surfing arena. It is a fairly insane wave. And what we learned from our studies in Hawaii was that the infrasound that comes from breaking wave scales, not necessarily with the high, but at breaking intensity. How hard is this wave breaking? And usually, if it's large, it breaks harder. But mostly, it's how hard is hitting the shelf? How hard is collapsing up open itself? And one thing we found out, for example, is that pipeline is like the perfect infrasound radiator, which we look at it to realize it's the nastiest thing. And so it all makes sense. So surf, anybody who is in the business of chasing waves can hear it the night before. It's going to be big tomorrow. Everything starts ringing. Everything starts resonating. Some of that is the ground, but some of it is infrasound, with that distance in the. I'm presumably, it's not just pipeline, which is important. You could also be studying the regular surf along the beaches in Hawaii. So even small breaking waves, as they crash either on the beach or they break off shore, would they make infrasound signals as well? That's correct. So the bigger they are, the meaner things are. In general, the rule is the deeper they go. So this is something that's going to be recurrent. The bigger it is, the meaner it is, the deeper it is. All right, so lower and lower. The other examples here like that huge volcanic eruption at bottom left on the screen or media are coming into the Earth's atmosphere. They must make very striking sound waves as they enter through the atmosphere. Just taking the wave analogy to the other extreme, you have the Tohoku earthquake and tsunami. And we had an infrasound signal, that giant wavelength. I mean, the scale of the atmosphere that arrived to Hawaii five hours before the tsunami is essentially an acoustic recursion to the tsunami wave. Which would give us an early warning signal if we had an array of instruments. Now, do you just have regular microphones for this kind of work? The second slide shows some of the toys I think you've built. Can you just explain some of the things which we're seeing in this illustration? All right, so you're looking at the infrasonic things. And this is on the left hand side are some of the equipment that we have traditionally used to recording for sound. And they consist of a microphone, a low frequency microphone, which doesn't kind of look like your microphone unless you like zoomed in with a microphone. Yeah, our sound code here in the studio is scratching their head saying that doesn't look like a microphone to me. Absolutely. And part of that has to do with the scale of the sound that we're trying to capture is on the order of tens to hundreds of meters. Okay. Yeah, yeah. It occupies a lot of space. So these things are miniscule compared to the scale of the sound we're trying to capture. And do you put them out in the field or have them in a lab or what's the deployment strategy you use? So on the left hand side we have the cylindrical things of the sensors and then the more square things are the things that turn it into bits and bytes. And then we deploy them, not necessarily a single stations, although we can do that, but as conglomerates of elements that are coherently like we have two ears and that helps us find directions. If we have more than two ears, we have four ears, we could tell heights much better. And so when we deploy them as a set of sensors that work together to be able to tell direction of arrival of a sound wave. So essentially with our sensors it came from the right, it came from the left. And you would put these sensors tens of meters or kilometers apart or on different continents, what's the spacing that you need? So we would put them on the ground, on the surface of the ground, listen to the atmosphere. Although some people put them on balloons, some people put them in all kinds of strange places. But the concept is you design the separation based on the scale of the sound you want to capture. So if you want to capture smarter scale sounds, so beyond the order of tens of meters. But if you're trying to record a clandestine nuclear test at distances of 2,000 kilometers, which a lot of these things are designed to do, then the distance between each element is 100 kilometers. So you end up with a very large opportunity to scale with a very large sound. So it would be comparable to, say, a radio telescope that astronomers might use or a seismic array that a geophysics person might be studying, earthquakes, that sort of thing. Yeah, so these are adaptable aperture telescopes that you have multiple elements. It's the same idea. You're looking at sound coming from different, from the same place of different stations and then putting it all together again. Now on the right hand side of that same figure are our new toys. These are toys that are essentially Internet of Things Capable. And one of the things that we are developing are cell phones, smart phones for their collection. And we just got lucky. They've been performing very well for two to five years. And I think we'll get back to the cell phones in the second half of the show. I think the third slide actually shows us what some of your data look like. And it doesn't particularly matter. We're looking at sound waves, it says, from the hooker. Can you explain all the nice colors and what the scale is on the left hand side? We're seeing not one frequency of sound, but many, is that correct? Yeah, this is the part where I put my expert goggles on and I look at this data and it's what we call an expert's rendition of the same wiggles that you'll imagine. On the bottom panel, you can see that there's a little black line and that's what you will get from any sunset. You have an MP3 and you put it on your recorder and you see wiggles. It's like, oh, cool. Yeah. Well, the very first wiggle that you see there on the left-hand side with the sharp onset, the first color that you see, that corresponds to a seismic wave that came from the Japanese earthquake. And so on the whole first stage in there on the left-hand side on the figure are earthquake waves arriving to Hawaii from Japan. And different paths that they take to the different layers in the earth. And so that earthquake was so big that it shook here in Hawaii and the microphones, well, they're moving up and down and that gives you a pressure differential. So we can record seismic. On the horizontal axis, we've got time early on the left, right on the right. Yes. And then the colors, might they be intensity? They tell you direction. They tell you the speed of propagation. They tell you a number of variables that give you reassurance that this is legit. This is a real signal. And that means that all the sensors are playing well together. And they're all telling me, this signal is coming from Japan and it's moving this fast. So it helps us, it's almost recognized seismic waves from acoustic waves. So on the left-hand side, early in time, the seismic waves get here fast. Here they are. Later in time, this massive infrasound wave. I mean, the scale of this wave is from the Earth's surface to the upper atmosphere. There is a wall of sound, literally, coming at us from Japan. And this thing arrives very deep and rings for a very long time. And it moves at the speed of sound. The typical tsunami moves at 200 meters per second. Sound moves at 340 meters per second. So it essentially outruns the tsunami and gets to us and says, hey, this thing really went off. So that's our second seismic wave. That tsunami advance warning, it may not tell us exactly it's heading straight for Hawaii, but it would at least give you an understanding of the magnitude of the event. If people tell you something wicked this way, it comes. The magnitude of the earthquake will probably be coming from the seismic. But what the infrasound tells you is, we had a really big displacement in the atmosphere. As you know, if plates rub against each other, the displacement is horizontal, not vertical. This is a measure of how much it moves vertically. All right. And we've had both Drudfire and Wett Butler on the show previously talking about tsunami risks to Hawaii. Your infrasound data, would they be available in near real time? Or does it take a lot of computer processing to understand what it is that they're telling you? It takes about an hour per thousand kilometers. So if you're looking for a way, it runs the tsunami, but there's still a time that it takes to get here. And part of recognizing the signal is knowing that it's there. When this happened, we've only seen this type of signal that clear twice, which was from Tohoku and then from Sumatra. So we first discovered it in Sumatra with the same network, global network. And then this is the second time we see it. That being said, there are groups in Japan who are deploying a system to use infrasound for early warning. And it's much closer to the source. So some of the data that is here is available to the Pacific Tsunami Warning Center, for example. So they have access to it. And so they will be the ones who get to choose is this useful to us? And then if necessary, then we can develop our products. Right, but it's another alternative technique whereby we can perhaps get a better understanding of severity. But let me stop you here, Milton, because we're getting near the mid-show break. So let me just remind the viewers, if you're watching think-tech Hawaii research in Manoa, I'm your host, Pete McGinnis-Mark. And my guest today is Dr. Milton Gases, who is a researcher, also in the Institute of Geophysics and Planetology, and Milton's at his field site. He's on the big island foot, joining us via Skype. And we'll be back to Milton in about a minute. So see you then. Hello, I'm Dave Stevens, host of the Cyber Underground. This is where we discuss everything that relates to computers that just kind of scare you out of your mind. So come join us every week here on ThinkTechHawaii.com 1 p.m. on Friday afternoons. And then you can go see all our episodes on YouTube, just look up the Cyber Underground on YouTube. All our shows will show up. And please follow us. We're always giving you current, relevant information to protect you. Keepin' you safe. Aloha. Aloha. My name is Mark Shklav. I'm the host of Think-Tech Hawaii's Law Across the Sea. Law Across the Sea comes on every other Monday at 11 a.m. Please join us. I like to bring in guests that talk about all types of things that come across the sea to Hawaii. Not just law, love, people, ideas, history. Please join us for Law Across the Sea, Aloha. And welcome back to Think-Tech Hawaii Research in Manoa. I'm your host, Pete McGinnis-Mark, and my guest today is Dr. Milton Garces. And we're talking about infrasound. Sound waves, which I is, cannot hear, but tell us lots and lots of geophysical information. So, Milton, as we were talking about the tsunami, it became clear to me that it would be really helpful if you had lots and lots of your toys, your sensors, spread out around the planet. And I'd like to pursue this a bit more in the second half of the show, because I believe you are hinting that we could use our cell phones to do this. Can you explain? I'm gonna dedicate this next little origin story to Margo, because she asked me once how I came up with this, and Margo, I didn't have a good story. That's right. So, one of the slides that showed earlier was the Russian meteor, the Shelyabins meteor. That thing was massive. It's about, you know, half a megaton of explosive yield equivalent of detonating over Russia. And they made a lot of people very nervous. The closest infrasound station was part of the Comprehensive Nuclear Test and Treaties International Monitoring System. It was in Kazakhstan, 600 kilometers away. And the signature was loud and clear. Over the next day, that giant explosion from this monster meteor went on to the world, not once, but twice. And we started, oh God, very excited about this. We don't get, we don't get at something like that very often. It's been the biggest explosion. Fortunately, yes. Yeah, yeah, it's kind of nerve-wracking, you know. This is a next secret Soviet facility, right? So, imagine that there was a moment of tension there. And so, when I looked at the way from the Nexus 5, just come out of Google, and they had a barometer in there. And I looked at this, and I looked at that, and I said, hey, we could have picked up this signal with a cell phone. And this is, this is just an illustration, presumably this is stylized, or are these real data that you're showing us on this cell phone? Oh no, this is real. So, this is live, and you can go to the App Store, or the Play Store, and type infrasound, and you can essentially get an application that will record infrasound for you. And if you have a barometer in your smartphone, you can get both the microphone data and the barometer data to record infrasound as deeply as you want. And while we don't do any advertising, I see RedVox. I believe you're associated with RedVox, is that correct? Well, the chain of this was, so we, we come up with this CD, and I was like, well, can we do this? And then the Accelerated UH is the University of Hawaii effort to try to commercialize the University of Hawaii idea some technology. So they said, hey, you should form a company. So we were the first class of the Accelerated UH and we found the RedVox out of that. And so we essentially worked with UH to bring this thing to market and try to go up with different ways of applying it. So now we have Android, now we have iPhones, recording infrasound. And this is so part of the whole University of Hawaii ecosystem to try to find a path to commercialization. Yeah, because one of the things which the university is trying to do is to create new jobs and businesses within the state of Hawaii. So RedVox was initiated by the University of Hawaii and you've developed this app. And what do you do with it? Oh, there are so many things to do with it. It's actually kind of funny. So do you have the next slide, please? So if we go. So these are, so this is one of the existing global networks. And if you look at it from this scale, it looks pretty dense, but when you drill in to the details, this is actually fairly sparse. There's always a need for more sensors. And these things do tend to get rather expensive. So we're trying to find a way that we can create a network very quickly using whatever everybody has in their hands, which is smartphones. So we're looking at a map of the globe and all the different symbols, whether they're green or red or blue. Some are already in place, but all of these would look like the set of toys you showed us in your second slide, where we're basically building pieces of hardware as one-off kinds of instruments. And then you have all the data which you have to contend with. So this particular network consists of four different types of systems. It has seismic and the water acoustics. It has in-person and also gas monitoring. And all these things are cohesive, in a sense, for this network, but they're all sparse. So if we want to build a more dense network, we have to wait for adaptable ways of doing it. So we're trying to supplement these beautiful networks that exist out there already by finding ways to do it on the fly as needed. Basically like you will fire up Google Maps to find out where you want to go. This is a way for us to collect data very quickly. And I bet your cell phone app actually uploads the data or you can find them on a website or something like that. So is this a current capability or something you're trying to build for the future? So let's go to the next slide and talk a little bit about the SpaceX Falcon Heavy. All right, here we got a nice NASA photograph of the launch a few weeks ago. It was a gorgeous, gorgeous thing. It's one of those things that at least makes me proud to be a human being, the fact that we can not just launch something into space but do a synchronized ballet landing of a... And this must make a large noise, not only right in Cape Canaveral, but around the surrounding area, I would guess. Yes, and we did not know how this was going to play out. As you already know, the initial odds of success for this was about 50-50. So we deployed as if it was going to play, maybe not really all go smoothly. And imagine if that had happened, that would have been something else. As it turned out, it went out very smoothly. All the power was distributed very evenly along the trajectory. So it made a sound that was actually not as loud as it could have been, had things gonna miss. So this is actually a very beautiful launch. We pick up the pick off and then the landing of the first stage. So if you go to the next slide and you can see a map with little cell phones. And your website, redfox.io, is that correct at the bottom? Yeah, okay, that's correct. I'm sure some of our viewers will want to log in and check it out. So if you download the app and start recording, the data will go to redfox.io and start processing automatically and become part of the whole community. And so what you're seeing there is a crowdsourced network. These are all people who have cell phones turned them on and so I'm just running for the background and then recording the whole launch and landing. And the red star on the island off to the right-hand side, just north of Cocoa Beach. That was the launch site. And the difference in the colors between the green and the white cell phones is. It's Android versus iPhone. Okay, so it works on both platforms, which is great. And what did you hear? Well, if you look to the last slide, and again, this is one of the things that I'll just explain with some details. Let's take a look, yes, okay. What do we have here in this slide? Well, I'm showing you one of our first test units. This is an iPod Touch. It's not even a cell phone, music player. So essentially it's a music player that has a microphone in it and is sitting over 20 kilometers away from the launch site, or quite a ways away. And what you can see in that figure, it's a time on the horizontal. And on the vertical, on the lower panel, it's the wave form. Again, if you have a sound file, you will see the wave form. And the time's in minutes, is that right? The time is in minutes, that's correct. So it takes a while for the sound to get to 20 kilometers away. And then what you're seeing is the whole launch sequence. It turns on, it goes off, it vanishes. And then later, you'll see this little spike that show up as a high intensity yellow. Yeah. And on the third panel, red, those, it does the reentry component. That's when the items start coming back down on earth. Unbelievable. And then the grand finale over there is that double entry. And somewhere in the cell over here, there's that core stage that hit the ocean at Mach 1 half. Uh-huh. But that's a little bit more advanced again, yeah. If you're a SpaceX engineer, for example, there must be an awful lot of technical information which you could pull out of that kind of infosound sonogram for want of a better word. Because you mentioned, had it exploded on the launch pad, it would have had a different acoustic signature from whether or not it was working correctly. And would you even be able to tell, say, if there was one of the boosters which wasn't quite functioning as well as the other two? When my car's not running properly, I can hear that it's not happy. Is the same true for the infosound sickness? I would think that that would be the case. And I would hope that the SpaceX engineers have a good set of microphones laying around the launch pad to record the performance variables on this. I doubt that they will share that with us. But if they wanted to, that would be a more complex. But this would be a great capability that you could provide to either SpaceX or to NASA or anybody else that you don't want to go into the field and have a whole array of instruments which then get fried as the rocket goes up. But infosound, you can stand off 10, 20 miles and still pick up these signatures. That sounds something that your company might be particularly interested in. Who knows? If you think of a volcano, it's an inverted rocket that never makes it, then that was the original premise for volcano monitoring, essentially. Just step away from the monster, don't get hurt, don't destroy your equipment, and then record from a distance. And so the beautiful thing is that we have never built the rocket even half or a fraction of as powerful as our bigger volcanoes on Earth. Those are the nastiest, biggest things. And we pick up those signatures everywhere on the planet now because they're so deep and so clear. So infosound is incredibly diverse. You've just shown us that you can study surf breaking on the ocean, on the coastline, or tsunamis or volcanoes, and then you closed with infosound of a rocket launch. There must be many other applications. So as we draw to the end of the show, Milton, you should come back and tell us some more about one of the other applications. Because I know you've spent a lot of time developing this instrumentation. Would you be wanting to come back some other time in a not too distant future? Of course. Oh, it's terrific. Well, I'm afraid we've come to the end of the show. So let me just remind our viewers, you've been watching Think Tech Hawaii research in Manoa. I've been your host, Pete McGinnis-Mark, and my guest today has been Dr. Milton Garces, who's a researcher within the Hawaii Institute Geophysics and Planetology. And we've been learning just a little bit about the fascinating field of infosound. So hopefully we can get Milton back sometime in the future. Until then, join you again next week. Goodbye for now.