WEBVTT 1 00:00:00.000 --> 00:00:02.860 Okay, good afternoon everybody. Thank you very much for turning up. 2 00:00:02.980 --> 00:00:05.840 My name is Dr Fiona Kerr and I work for the Adelaide University 3 00:00:06.540 --> 00:00:10.460 as a systems and neural complexity specialist. So we're here today 4 00:00:10.960 --> 00:00:14.640 to listen to some fantastic good news about technology 5 00:00:14.640 --> 00:00:18.900 and about the use of drones. So we'll go into some of the wonderful things that 6 00:00:18.900 --> 00:00:21.680 they're doing because as with other sorts of technology there's the good and 7 00:00:21.680 --> 00:00:24.980 the bad of everything. So this afternoon is about some of the really positive 8 00:00:24.980 --> 00:00:27.760 things that people are doing with technologies. 9 00:00:27.760 --> 00:00:31.800 So I'm going to start with Carl. So if you want to 10 00:00:32.340 --> 00:00:35.420 introduce yourselves. My name is Carl Sammet. 11 00:00:35.820 --> 00:00:39.320 I'm an academic working at Flinders University in the School of Computer 12 00:00:39.320 --> 00:00:43.300 Science, Engineering and Maths and my area of research, in fact my 13 00:00:43.300 --> 00:00:47.580 passion is about autonomous vehicles, mainly looking at autonomous marine 14 00:00:47.580 --> 00:00:51.680 vehicles. And my name is Dan Squire. I've 15 00:00:51.680 --> 00:00:54.980 run a startup business called Drones Over Water. 16 00:00:55.360 --> 00:00:57.560 We're focusing on trying to use drones in the water 17 00:00:57.560 --> 00:00:57.740 industry. 18 00:00:57.760 --> 00:01:01.960 And provide a safer option and utilise the technology in a good way. 19 00:01:02.180 --> 00:01:07.560 So Carl, if you would like to run through your show and give us a grounding and 20 00:01:07.560 --> 00:01:09.280 then we can have a really good conversation, everybody. 21 00:01:09.760 --> 00:01:13.340 Right, I'd like to start off with this scene and some of you may be familiar with this. 22 00:01:14.300 --> 00:01:17.700 So imagine you're out at sea on a fishing boat or on 23 00:01:18.560 --> 00:01:23.160 some other merchant vessel or military vessel and you've got to work with this 24 00:01:23.160 --> 00:01:27.560 kind of environment. It's not exactly a good way 25 00:01:27.560 --> 00:01:27.740 to do it. 26 00:01:29.380 --> 00:01:45.700 You'd have to spend a long time travelling out there, then spend a brief amount of time doing the actual work on a fishing vessel and then coming back again. So it's going to take quite a lot of stress on the people working on board these ships. 27 00:01:46.320 --> 00:01:57.540 What I'd like to do is to look at a way that perhaps we can replace some of the people working on these ships, take them out of danger and replace them with robots that can do the work without 28 00:01:58.240 --> 00:02:01.120 incurring the risks to the human operators. 29 00:02:01.820 --> 00:02:07.240 So the rationale for looking at marine robots is to be able to remove the human beings from dangerous 30 00:02:07.240 --> 00:02:10.700 environments. These days the robotic vehicles are getting 31 00:02:11.740 --> 00:02:17.320 more sophisticated, they're smaller, they're lighter, they're much less expensive than a 32 00:02:17.320 --> 00:02:20.660 manned vessel. I'll give you an explanation of one later on. 33 00:02:20.840 --> 00:02:24.800 They're more survivable, so you don't need to build these vehicles to have 34 00:02:24.800 --> 00:02:27.320 all the living accommodation or the life support. 35 00:02:31.980 --> 00:02:57.000 And I think that's why we think that we need to think about these people permanently, 36 00:02:57.000 --> 00:03:02.720 capacity. They can also be used in an expendable way. So you wouldn't use a human being in a risky 37 00:03:02.720 --> 00:03:09.220 situation, but you might be able to use a robot to do that. Would you send out a crew to rescue 38 00:03:09.220 --> 00:03:14.820 people in a storm, or would you send out a robot? Unfortunately, in the maritime environment, 39 00:03:15.060 --> 00:03:20.320 in a lot of cases, we don't have very good communication systems between the ground and 40 00:03:20.320 --> 00:03:26.700 the ships. You've got Wi-Fi, but that's limited in terms of its range to a few kilometers. 41 00:03:27.540 --> 00:03:30.920 You have longer range radio systems, but they're limited in terms of bandwidth. 42 00:03:31.280 --> 00:03:38.000 If we work underwater, we have no electromagnetic communication systems. We can only rely on 43 00:03:38.000 --> 00:03:43.220 acoustic communication systems. That's very low bandwidth systems. So we're talking about 44 00:03:43.220 --> 00:03:50.480 the kind of bandwidth that you would have on a dial-up modem back in the 1980s. Not very good 45 00:03:50.480 --> 00:03:56.340 for sending video back, certainly not live video. So that means that we're going to take the human 46 00:03:56.340 --> 00:03:56.620 operator. 47 00:03:57.000 --> 00:04:00.740 We're out of the loop. We need vehicles that are capable of doing things for themselves, 48 00:04:01.040 --> 00:04:04.240 essentially without a human being involved in supervising them. 49 00:04:05.780 --> 00:04:10.240 The vehicles have to be able to make onboard decisions, and they have to do it with very 50 00:04:10.240 --> 00:04:15.760 fast response times. The only information we need to send back to the operator is a 51 00:04:15.760 --> 00:04:22.120 cut-down version of a summarized version of the data that the robot is seeing and collecting. 52 00:04:22.840 --> 00:04:26.820 Because we've got all this data coming back, we need not only to summarize it, but we need to 53 00:04:26.820 --> 00:04:28.000 think about it in terms of how we think it works, and think about it in terms of how we think it 54 00:04:28.000 --> 00:04:30.460 So we need to think about it in terms of how we think it works, and think about it in terms of 55 00:04:31.820 --> 00:04:37.020 So we need to think about it in terms of how we think it works, and think about it in terms of 56 00:04:37.020 --> 00:04:37.500 how we think it works, and think about it in terms of how we think it works. 57 00:04:38.020 --> 00:04:40.860 So we need to think about it in terms of how we think it works, and think about it in terms of 58 00:04:40.860 --> 00:04:41.120 how we think it works, and think about it in terms of how we think it works. 59 00:04:41.120 --> 00:04:43.820 So we need to think about it in terms of how we think it works, and think about it in terms of 60 00:04:43.820 --> 00:04:52.980 how we think it works, and think about it in terms of how we think it works. 61 00:04:52.980 --> 00:04:58.040 fashion. They've changed the way that we're doing the kind of operations that we used to do in the 62 00:04:58.040 --> 00:05:02.760 past. That's not necessarily a bad thing. In fact, it's quite a good thing. For instance, I gave you 63 00:05:02.760 --> 00:05:09.400 the scenario of, would you send out a human being, put them in a risky situation to do a job that is 64 00:05:09.400 --> 00:05:14.760 essential to rescue somebody else, or even to go out and catch fish in stormy weather? 65 00:05:16.140 --> 00:05:19.920 These are some of the existing vehicles. So I'm going to look at three types of vehicles. 66 00:05:19.920 --> 00:05:24.940 The first type are remotely operated vehicles. Now these are tethered back to a mothership. 67 00:05:26.540 --> 00:05:31.440 The reason I want to show these is because I want to describe the kind of complexity we have. 68 00:05:31.700 --> 00:05:35.720 These are very low complexity in terms of the autonomy that they have. They're essentially 69 00:05:35.720 --> 00:05:40.040 controlled by a pilot on board the ship. Most of these are developed for the oil and gas industry. 70 00:05:40.480 --> 00:05:46.100 The bottom one over there, bottom right, is about the size of about a three-story house. 71 00:05:46.960 --> 00:05:49.800 It's designed to dig trenches for oil and gas pipelines. 72 00:05:49.920 --> 00:05:54.420 There's only a couple of them in the world. Top right, the green one, that's one that's used for 73 00:05:54.420 --> 00:06:00.780 research applications. It costs about 60,000 Australian dollars. It's a small vehicle. 74 00:06:00.880 --> 00:06:07.820 It can be launched from a tinny, basically. They are expensive. These are autonomous underwater 75 00:06:07.820 --> 00:06:13.340 vehicles. So now we have no communication with them other than acoustic communication systems. 76 00:06:13.680 --> 00:06:18.200 They have to operate by themselves, so they have to be very smart. And there's a range of them. 77 00:06:18.600 --> 00:06:19.900 Some developed for the oil and gas industry. Some developed for the oil and gas industry. 78 00:06:19.920 --> 00:06:24.940 And some developed for military applications. Quite a few of them being developed now for 79 00:06:24.940 --> 00:06:27.780 environmental monitoring applications, which is my area of interest. 80 00:06:29.800 --> 00:06:34.520 They all came out of universities. So they're all spin-offs from universities, whether from 81 00:06:34.520 --> 00:06:40.320 Norway, from Iceland, from Europe, or from America. And they are expensive because, again, 82 00:06:40.360 --> 00:06:44.380 as you can see up on the top left, there's only about 40 companies worldwide that produce 83 00:06:44.380 --> 00:06:49.060 autonomous underwater vehicles. And only about 10 of them actually produce them in enough 84 00:06:49.060 --> 00:06:49.900 numbers to be able to operate. And they're all developed for military applications. 85 00:06:49.900 --> 00:06:50.180 So they're all spin-offs from universities, whether from Norway, from Africa, or from America. 86 00:06:50.180 --> 00:06:53.860 to satisfy the requirements. And none of them are in Australia, again. 87 00:06:54.740 --> 00:07:02.100 These are unmanned surface vessels. So we saw the underwater ones. These are their surface 88 00:07:02.100 --> 00:07:08.640 counterparts. And they're relatively new. These are mostly military applications. But again, 89 00:07:08.820 --> 00:07:13.460 there are, and I'll show you what we're working on, vehicles that are being used for environmental 90 00:07:13.460 --> 00:07:19.480 applications. The reason I wanted to show you this is that the bottom left one, which was only launched 91 00:07:19.900 --> 00:07:28.160 recently by the U.S., designed for the U.S. Navy as a submarine hunter, costs about $10,000 a day to 92 00:07:28.160 --> 00:07:35.520 operate. It's a sea hunter vehicle. That replaces a destroyer for the same purpose, which costs 93 00:07:35.520 --> 00:07:42.080 something like a quarter of a million dollars to operate per day. So enough of what there is out 94 00:07:42.080 --> 00:07:46.500 there at the moment. I want to look at our work a bit. So we started about 12 years ago working on 95 00:07:46.500 --> 00:07:47.220 underwater vehicles. 96 00:07:49.900 --> 00:07:55.020 In fact, one of the big projects we started out with was a project for the CSIRO, which was 97 00:07:55.020 --> 00:08:00.900 World for Emotions flagship, looking at subsea pipelines, moving the wellheads and the pipelines 98 00:08:00.900 --> 00:08:06.700 further away from the continental shelf. And you quickly drop off down to about 3,000 and 5,000 99 00:08:06.700 --> 00:08:12.520 meters. You can't have surface rigs for that. So everything has to be done on the seabed. 100 00:08:13.100 --> 00:08:18.680 It's well out of reach of human operators. So essentially, you need some kind of system 101 00:08:20.500 --> 00:08:25.400 preferably an autonomous underwater vehicle to go down and scan the pipeline, see if it's moved, 102 00:08:25.520 --> 00:08:30.440 see if there's any damage, any oil leaks, and look at the wellheads as well. 103 00:08:31.240 --> 00:08:37.480 So we developed technology to be able to follow the pipelines using sonar and using cameras to be 104 00:08:37.480 --> 00:08:38.660 able to identify that. 105 00:08:39.840 --> 00:08:46.860 This is more of an environmental application. Now, this is not our work. This is done by a researcher 106 00:08:46.860 --> 00:08:48.200 up at Queensland at QUT. 107 00:08:48.640 --> 00:08:49.160 But, 108 00:08:49.960 --> 00:08:55.400 it's a similar area to what we've got. So I've used his images here because I wanted to show you 109 00:08:55.400 --> 00:09:01.300 a common problem. Most environmental agencies use snorkelers or divers from the community to be able 110 00:09:01.300 --> 00:09:08.460 to go out and collect data. You get currents, which push the diver, of course. So top left, 111 00:09:08.660 --> 00:09:16.120 sorry, on the left-hand side, we've got an image showing three different runs with, on one occasion 112 00:09:16.120 --> 00:09:19.880 in June, the diver being swept away by a river. So, it's a very similar situation. So, it's a very 113 00:09:21.760 --> 00:09:24.440 similar situation. So, it's a very similar situation. So, it's a very similar situation. So, it's a very 114 00:09:26.560 --> 00:09:33.820 similar situation. So, it's a very similar situation. So, it's a very similar situation. So, it's a very 115 00:09:33.820 --> 00:09:37.180 similar situation. So, it's a very similar situation. So, it's a very similar situation. So, it's a very 116 00:09:37.180 --> 00:09:37.660 similar situation. So, it's a very similar situation. So, it's a very similar situation. So, it's a very 117 00:09:37.660 --> 00:09:43.460 similar situation. So, it's a very similar situation. So, it's a very similar situation. So, it's a very 118 00:09:43.460 --> 00:09:49.860 similar situation. So, it's a very similar situation. So, it's a very similar situation. So, it's a very 119 00:09:49.860 --> 00:09:54.500 what the divers collected and the one further that to the right is what the AUV is collected 120 00:09:54.500 --> 00:10:01.420 the data is more precise it's more representative of what actually is down there so they're 121 00:10:01.420 --> 00:10:07.280 collecting images of sea grasses and classifying those at about the same time this this was 2012 122 00:10:07.280 --> 00:10:11.900 period we were looking at our own navigation system for autonomous underwater vehicles and 123 00:10:11.900 --> 00:10:17.320 we developed one which improves the accuracy so as I said we don't have GPS on the water so how do we 124 00:10:17.320 --> 00:10:23.360 navigate we use the inertial navigation systems on board the vehicles we use sonar in fact a 125 00:10:23.360 --> 00:10:28.360 version of that called doppler and sometimes we can use cameras as well to allow us to navigate 126 00:10:29.540 --> 00:10:36.240 and if you look at the red line that's so the vehicle is doing a rest of scan what is known as a 127 00:10:36.240 --> 00:10:43.220 lawn mowing approach it's doing about 15 kilometers over here the red one starts off and ends up 128 00:10:43.800 --> 00:10:47.200 so it goes all the way does the rest of scan comes back again ends up about 129 00:10:47.320 --> 00:10:52.180 15 meters away from where it should be that's the error over the entire 15 kilometer transit 130 00:10:53.980 --> 00:10:59.080 hours end up about 10 meters off from its starting point so that's the error we get at the end of the 131 00:10:59.080 --> 00:11:04.060 day we need good accuracy we're collecting data we need to know exactly where it is when we collect it 132 00:11:04.620 --> 00:11:10.680 the vehicles have to stay down as long as possible in most cases the vehicle has to come back up to 133 00:11:10.680 --> 00:11:16.620 the surface get a gps fix correct its navigation go back down again so we're trying to minimize 134 00:11:16.620 --> 00:11:17.300 the number of times we need to navigate 135 00:11:17.300 --> 00:11:20.320 that has to come up, get it to spend longer on the water doing its work. 136 00:11:21.500 --> 00:11:21.860 Okay. 137 00:11:22.940 --> 00:11:25.200 Here's another example of some of the work that we're doing. 138 00:11:26.220 --> 00:11:28.420 So we've got a scene over there of a harbor. 139 00:11:28.500 --> 00:11:29.980 It's actually Apra Harbor in Guam. 140 00:11:31.120 --> 00:11:32.360 We picked this as an example. 141 00:11:32.440 --> 00:11:33.180 We've got a petimetry. 142 00:11:33.640 --> 00:11:35.700 That's a 3D map of the seabed. 143 00:11:36.620 --> 00:11:39.220 And the task there, for instance, would be to get a mission 144 00:11:39.220 --> 00:11:42.480 for the vehicle to go through and navigate through the harbor, 145 00:11:42.560 --> 00:11:44.640 come to the other end down at the bottom over here. 146 00:11:46.200 --> 00:11:48.600 Now, I could sit down and plot this out carefully 147 00:11:48.600 --> 00:11:50.640 to make sure that the vehicle's not going to bump into anything. 148 00:11:51.120 --> 00:11:53.060 Really difficult to do. 149 00:11:53.500 --> 00:11:55.540 Or else I can give it to one of our mission planners, 150 00:11:55.680 --> 00:11:57.160 a system that looks at the petimetry, 151 00:11:57.320 --> 00:11:59.180 works out the best possible route for itself, 152 00:11:59.760 --> 00:12:01.860 works out the tasks that the vehicle has to do, 153 00:12:01.900 --> 00:12:03.720 and then go and navigate through all that. 154 00:12:04.320 --> 00:12:05.900 It can do that in a matter of minutes 155 00:12:05.900 --> 00:12:08.780 as opposed to the amount of time I would have had to do it by hand. 156 00:12:09.480 --> 00:12:11.020 And I know that our system is safer. 157 00:12:12.260 --> 00:12:14.000 Now, the scenario here where we've got 158 00:12:14.000 --> 00:12:14.600 three vehicles. 159 00:12:14.640 --> 00:12:16.620 One coming out from the coast, 160 00:12:17.660 --> 00:12:19.060 a surface vehicle to collect, 161 00:12:19.800 --> 00:12:21.180 two underwater vehicles, 162 00:12:22.260 --> 00:12:23.900 and using the currents 163 00:12:23.900 --> 00:12:27.640 to actually make the best possible use of the currents 164 00:12:28.260 --> 00:12:31.140 to get to the collection point to pick up the vehicle. 165 00:12:31.240 --> 00:12:33.340 So the three red lines intercept at the point 166 00:12:33.340 --> 00:12:34.980 that is suitable for all three vehicles. 167 00:12:36.080 --> 00:12:38.360 We're using situation awareness to identify 168 00:12:38.360 --> 00:12:39.960 what the vehicle has to do 169 00:12:39.960 --> 00:12:43.100 to be able to change its plan 170 00:12:43.100 --> 00:12:44.360 while it's doing it. 171 00:12:44.640 --> 00:12:46.720 It's no good saying, giving it a set plan. 172 00:12:46.860 --> 00:12:48.000 There are currents in the water 173 00:12:48.000 --> 00:12:49.540 and those currents will change over time. 174 00:12:51.080 --> 00:12:53.460 Sometimes storm conditions will change those 175 00:12:53.460 --> 00:12:55.340 between beyond what we expect. 176 00:12:56.500 --> 00:12:58.600 Also, the vehicle has a limited battery life. 177 00:12:58.640 --> 00:13:00.320 Sometimes that battery life will deplete 178 00:13:00.320 --> 00:13:02.160 because it has to do extra work 179 00:13:02.160 --> 00:13:03.260 that we can't predict in advance. 180 00:13:03.740 --> 00:13:06.700 So this vehicle has to be able to change its mission plan, 181 00:13:07.580 --> 00:13:09.880 try to do as much of the tasks as it has, 182 00:13:10.040 --> 00:13:10.820 change it online, 183 00:13:11.460 --> 00:13:14.100 and get back to its destination. 184 00:13:14.100 --> 00:13:16.980 Without losing too much time. 185 00:13:17.780 --> 00:13:20.860 Okay, finally I'll come to one of our vehicles. 186 00:13:21.000 --> 00:13:21.800 So this is Top Cat. 187 00:13:21.920 --> 00:13:23.540 This is a boat that we have at Flinders University. 188 00:13:24.060 --> 00:13:26.140 We actually got this from the Office of Naval Research. 189 00:13:26.380 --> 00:13:30.820 And we got the bottom part really from a company in the US 190 00:13:30.820 --> 00:13:33.940 and we've adapted that for our applications. 191 00:13:34.800 --> 00:13:37.320 Up at the top we've got a very accurate GPS system. 192 00:13:37.480 --> 00:13:39.140 It gives us one centimeter accuracy 193 00:13:39.140 --> 00:13:40.060 in terms of positioning. 194 00:13:40.800 --> 00:13:41.680 We've got a radar. 195 00:13:41.800 --> 00:13:42.520 We've also got 196 00:13:42.520 --> 00:13:43.760 a radar. 197 00:13:44.100 --> 00:13:45.980 Somewhere up here, if you can see it, 198 00:13:46.060 --> 00:13:50.900 is a little cylindrical thing, 199 00:13:50.940 --> 00:13:51.540 which is a lidar, 200 00:13:51.540 --> 00:13:54.280 which gives us 100 meters around the vehicle, 201 00:13:54.380 --> 00:13:57.040 a 3D map of what's happening around the vehicle. 202 00:13:58.380 --> 00:14:00.440 So between the radar and the lidar, 203 00:14:00.440 --> 00:14:03.240 we can get very good imaging of objects around the vehicle, 204 00:14:03.340 --> 00:14:04.780 including people in the water. 205 00:14:05.120 --> 00:14:07.480 There's a little boy, red boy, up top. 206 00:14:07.600 --> 00:14:09.020 We can actually see that with the radar. 207 00:14:09.740 --> 00:14:12.240 So imagine that's about the same size as a human head. 208 00:14:13.360 --> 00:14:14.080 So we can get a lot of images. 209 00:14:14.080 --> 00:14:17.160 We can quite satisfactorily navigate around that person 210 00:14:17.160 --> 00:14:18.520 if there is somebody in the water. 211 00:14:19.040 --> 00:14:20.920 The vehicle is also capable of deploying 212 00:14:20.920 --> 00:14:22.560 sonar systems into the water, 213 00:14:22.700 --> 00:14:27.080 all kinds of environmental sensing equipment into the water. 214 00:14:28.100 --> 00:14:29.460 It can measure wind speed. 215 00:14:29.780 --> 00:14:32.020 So effectively, this is a very good instrument 216 00:14:32.020 --> 00:14:33.940 for collecting environmental data. 217 00:14:34.840 --> 00:14:38.280 And we're using that for a number of applications. 218 00:14:38.600 --> 00:14:41.340 We've also got a rather fun project at the moment. 219 00:14:41.620 --> 00:14:43.240 So let me just show you this. 220 00:14:43.240 --> 00:14:45.600 This is some of the Liar imaging that the boat took. 221 00:14:46.460 --> 00:14:49.080 So this is scanning with a laser scanner around the boat. 222 00:14:49.180 --> 00:14:50.260 This is on the Torrens River. 223 00:14:50.940 --> 00:14:54.060 We've got rowing boats down in the middle of the river as well, 224 00:14:54.160 --> 00:14:55.000 shown over there. 225 00:14:55.800 --> 00:14:58.260 This is a radar map taken at West Lakes. 226 00:14:59.420 --> 00:15:02.240 So the boat's traveling down the middle over here, 227 00:15:02.360 --> 00:15:05.520 and the white areas indicate the radar scan of the docks 228 00:15:05.520 --> 00:15:08.360 and the houses around West Lakes. 229 00:15:09.020 --> 00:15:11.340 And then we've got bathymetry data. 230 00:15:11.480 --> 00:15:13.140 So we've put on a small, 231 00:15:13.240 --> 00:15:15.880 full sonar onto that to collect depth data below the boat. 232 00:15:16.740 --> 00:15:18.340 So here's the fun project that we have. 233 00:15:18.460 --> 00:15:20.840 We're actually working on a competition called AUVSI. 234 00:15:21.020 --> 00:15:22.400 It's going to be in Hawaii this year. 235 00:15:22.740 --> 00:15:25.160 We've got a team of students building the autonomy for the boat, 236 00:15:25.320 --> 00:15:28.760 going out to the competition, working with other universities, 237 00:15:28.960 --> 00:15:31.780 to allow the vehicle to go into this obstacle area, 238 00:15:32.680 --> 00:15:33.820 navigate around buoys. 239 00:15:33.860 --> 00:15:35.620 So it has to follow collision regulations 240 00:15:35.620 --> 00:15:37.420 that normal ships would apply to. 241 00:15:37.540 --> 00:15:38.860 It has to find underwater objects. 242 00:15:39.020 --> 00:15:40.220 It has to dock by itself. 243 00:15:41.640 --> 00:15:43.220 It's got to do a whole range of things. 244 00:15:43.240 --> 00:15:46.860 And these are students anywhere between first year 245 00:15:46.860 --> 00:15:48.880 and postgraduate level working on this project. 246 00:15:49.400 --> 00:15:52.080 It's quite challenging for them, and also good fun. 247 00:15:52.860 --> 00:15:53.960 Here's where we're going next. 248 00:15:54.960 --> 00:15:56.260 So we've got the boat. 249 00:15:56.800 --> 00:15:59.820 We're looking at putting a quadrotor on the boat, 250 00:15:59.900 --> 00:16:02.180 allowing that to take off from the back of the boat, 251 00:16:03.560 --> 00:16:07.140 survey an area, come back again, recharge, go back out again. 252 00:16:07.200 --> 00:16:09.760 So now we can cover with a quadrotor very large areas. 253 00:16:11.240 --> 00:16:13.100 Also employing a small ROV, 254 00:16:13.100 --> 00:16:15.900 so we can deploy that from the boat 255 00:16:16.540 --> 00:16:18.580 and allow it to go down and inspect things 256 00:16:18.580 --> 00:16:20.400 that the sonar system might see and think, 257 00:16:20.540 --> 00:16:22.100 these are interesting things to look at. 258 00:16:22.920 --> 00:16:23.820 Seagrasses, for instance. 259 00:16:25.880 --> 00:16:28.660 Also allowing it to collaborate with underwater vehicles as well, 260 00:16:28.720 --> 00:16:30.220 so they can recharge from the boat. 261 00:16:30.560 --> 00:16:32.260 This extends the area of operation, 262 00:16:32.480 --> 00:16:33.300 not just for the boat, 263 00:16:33.380 --> 00:16:35.260 but for all the other vehicles working with it. 264 00:16:36.400 --> 00:16:37.400 So that's our future. 265 00:16:38.200 --> 00:16:39.160 Thank you for your time. 266 00:16:41.760 --> 00:16:42.800 Thank you, Carl. 267 00:16:43.360 --> 00:16:48.000 Now, Daniel, would you like to give us your knowledge and experience? 268 00:16:48.920 --> 00:16:50.280 Yeah, I'll share what I can. 269 00:16:51.200 --> 00:16:53.100 Firstly, I'll start off with a little bit of a story 270 00:16:53.100 --> 00:16:55.160 about myself and how I got here. 271 00:16:56.060 --> 00:16:58.660 Finished high school, wasn't quite sure what I wanted to do, 272 00:16:58.700 --> 00:17:01.780 so lucky enough, a mate dragged me to a two-million-acre sheep station 273 00:17:01.780 --> 00:17:02.960 in the middle of Western Australia 274 00:17:04.520 --> 00:17:06.860 and taught me to be a man, you know, grow up out there. 275 00:17:06.940 --> 00:17:09.040 And I worked in agriculture for a couple of years, 276 00:17:09.040 --> 00:17:10.300 worked for APB Grain. 277 00:17:10.640 --> 00:17:14.780 Then I came back and ended up working in the Merchant Navy. 278 00:17:15.920 --> 00:17:18.180 So I travelled around the seas on big ships 279 00:17:18.180 --> 00:17:19.980 and then ended up in the oil and gas industry. 280 00:17:20.620 --> 00:17:23.520 Now, when I was a kid, I always flew remote control aeroplanes, 281 00:17:23.520 --> 00:17:26.460 so I thought that, you know, it's a fun, legible thing I like to do. 282 00:17:27.080 --> 00:17:29.460 God, it'd be fun to make some money out of this one day. 283 00:17:29.580 --> 00:17:31.160 So when I got to the oil and gas industry, 284 00:17:31.620 --> 00:17:32.840 I had been following drones 285 00:17:32.840 --> 00:17:36.680 and I'd been flying quadcopters and planes when I was at home, 286 00:17:37.520 --> 00:17:39.020 looking into it, doing a lot of research, 287 00:17:39.040 --> 00:17:41.660 and I saw they were being used in the oil and gas industry. 288 00:17:42.300 --> 00:17:45.740 So I came home, ended up meeting my wife, 289 00:17:45.820 --> 00:17:47.660 and so I decided that going away all the time 290 00:17:47.660 --> 00:17:49.100 probably wasn't the best idea. 291 00:17:49.540 --> 00:17:51.940 So I came home and still had this idea in my head 292 00:17:51.940 --> 00:17:54.260 that I wanted to use drones in some sort of application. 293 00:17:56.340 --> 00:17:57.720 Got a job in the water industry. 294 00:17:58.360 --> 00:18:00.800 I now work at Liglinilg Wastewater Treatment Plant, 295 00:18:00.960 --> 00:18:04.020 so I deal with a lot of crap all day, but it's a great job 296 00:18:04.020 --> 00:18:06.080 and it gives me a lot of experience 297 00:18:06.080 --> 00:18:08.300 and knowledge and connection in the water industry. 298 00:18:09.040 --> 00:18:12.500 So I was in the water industry with this passion for drones 299 00:18:12.500 --> 00:18:14.580 and passions for autonomous vehicles 300 00:18:14.580 --> 00:18:18.160 and thinking, you know, there's got to be an application here. 301 00:18:18.800 --> 00:18:22.620 Lucky enough, Linda's University NVI, New Venture Institute, 302 00:18:23.960 --> 00:18:25.880 run their Venture Dawn program, 303 00:18:26.040 --> 00:18:29.240 so I applied to go in there, got in there, 304 00:18:29.300 --> 00:18:31.020 and in that program you develop your business 305 00:18:31.020 --> 00:18:34.420 from basically just an idea to either a minimal viable product 306 00:18:34.420 --> 00:18:37.320 or trying to get it ready to be released to the world. 307 00:18:37.600 --> 00:18:39.020 So lucky enough, I did that program, 308 00:18:39.020 --> 00:18:39.680 and it was great. 309 00:18:39.740 --> 00:18:41.060 It got me in touch with lots of mentors 310 00:18:41.060 --> 00:18:44.360 and very clever people 311 00:18:44.360 --> 00:18:47.580 and very helpful people around Adelaide. 312 00:18:48.240 --> 00:18:51.980 So then I ended up getting to the end of the program, 313 00:18:52.260 --> 00:18:53.960 which the end of the program is a pitching competition, 314 00:18:54.180 --> 00:18:57.400 so I got to stand up in front of 300, 400 very important people 315 00:18:58.020 --> 00:18:59.920 and talk very well, which I sometimes do. 316 00:19:01.920 --> 00:19:04.480 And the prize for winning that pitching competition 317 00:19:04.480 --> 00:19:06.360 was a trip to the US, which I did win. 318 00:19:06.360 --> 00:19:09.620 So up against about 40 other competitors, 319 00:19:09.740 --> 00:19:11.620 I ended up winning and getting that trip, 320 00:19:11.680 --> 00:19:12.780 which was a fantastic trip. 321 00:19:12.880 --> 00:19:15.160 So on that trip, we got to fly to the US 322 00:19:15.160 --> 00:19:18.020 and meet with investors and other people over there, 323 00:19:18.120 --> 00:19:21.460 and lucky enough got to get to talk to some people in Texas, 324 00:19:21.480 --> 00:19:22.540 and I'll come back to that. 325 00:19:22.640 --> 00:19:26.300 But the business that I run is called Drones Over Water. 326 00:19:26.340 --> 00:19:29.140 So what we've developed is using drones 327 00:19:29.140 --> 00:19:32.000 to do water analysis and water samples for the water industry. 328 00:19:32.620 --> 00:19:35.180 So basically, as Carl was talking about before, 329 00:19:36.140 --> 00:19:39.160 it's the main focus that I started off with was safety. 330 00:19:39.340 --> 00:19:41.720 At this point in time, anywhere in Australia 331 00:19:41.720 --> 00:19:43.240 when you need to go and take a water sample 332 00:19:43.240 --> 00:19:45.380 or do water analysis on any water course, 333 00:19:45.520 --> 00:19:49.140 so for me in SA Water, when it comes to our reservoirs 334 00:19:49.140 --> 00:19:50.180 or our wastewater treatment plants, 335 00:19:50.220 --> 00:19:54.160 where we've got lagoons and sometimes hazardous waters, 336 00:19:54.280 --> 00:19:55.600 not as hazardous as other places, 337 00:19:55.760 --> 00:19:57.560 but someone goes out in a little boat 338 00:19:57.560 --> 00:20:00.880 or hangs sensors over the side of a dam, 339 00:20:01.440 --> 00:20:02.800 and that can be dangerous. 340 00:20:03.020 --> 00:20:05.160 And also it puts human error into it, 341 00:20:05.180 --> 00:20:09.820 and you've got a problem there that you can eliminate quite simply, 342 00:20:09.920 --> 00:20:11.780 and that simply is by doing it with a drone. 343 00:20:12.100 --> 00:20:14.920 So we've developed a program so that the drones can go out, 344 00:20:15.580 --> 00:20:16.740 either take a sample, 345 00:20:16.820 --> 00:20:19.500 or the more technology I've been working with 346 00:20:19.500 --> 00:20:20.660 is actually do water analysis. 347 00:20:20.780 --> 00:20:22.680 So the drone will go out and land on the water 348 00:20:22.680 --> 00:20:26.780 and give you feedback on what parameters are in that water, 349 00:20:26.840 --> 00:20:30.560 so things like pH conductivity, dissolved oxygen 350 00:20:30.560 --> 00:20:34.260 and other parameters that we would use as a water operator. 351 00:20:35.180 --> 00:20:37.100 So we can use these on water courses around, 352 00:20:37.800 --> 00:20:38.920 as I said, with SA Water, 353 00:20:39.040 --> 00:20:41.100 but also the Murray-Darling Basin Authority 354 00:20:41.480 --> 00:20:42.700 has had a lot of interest in this, 355 00:20:43.600 --> 00:20:45.080 and a lot of mining companies, 356 00:20:45.280 --> 00:20:50.040 because there's a lot of big water storages 357 00:20:50.040 --> 00:20:51.640 that are not safe to go on. 358 00:20:51.840 --> 00:20:53.020 So at this point in time, 359 00:20:53.060 --> 00:20:53.740 those water courses, 360 00:20:54.780 --> 00:20:56.900 that big body of water is just sitting there, 361 00:20:57.000 --> 00:20:58.240 no one knows what's in it, 362 00:20:58.280 --> 00:20:59.240 or not very well, 363 00:20:59.300 --> 00:21:00.860 because you can't go out into it and test it. 364 00:21:01.260 --> 00:21:03.200 So with this system, we'll be able to fly out 365 00:21:03.200 --> 00:21:04.280 and go out and test that water. 366 00:21:05.540 --> 00:21:10.640 I've also been working with promoting the STEM subjects 367 00:21:10.640 --> 00:21:12.700 in high school and talking to school kids about that, 368 00:21:13.540 --> 00:21:15.980 and also trying to promote drone safety as well, 369 00:21:16.040 --> 00:21:18.960 just through social media and other things like that, 370 00:21:19.000 --> 00:21:20.680 because I think that's something I'm a bit passionate about. 371 00:21:20.860 --> 00:21:22.280 But that's a little bit about what I do. 372 00:21:23.200 --> 00:21:25.440 I'm sure I'm probably better at answering questions, 373 00:21:25.560 --> 00:21:27.260 because I'm not as good at probably presenting myself 374 00:21:27.260 --> 00:21:28.440 when I'm not trying to pitch. 375 00:21:29.460 --> 00:21:30.860 But that's my story at this stage. 376 00:21:30.920 --> 00:21:32.160 But yeah, feel free to ask me any questions 377 00:21:32.160 --> 00:21:33.080 when we get to that stage. 378 00:21:36.780 --> 00:21:37.300 Thank you. 379 00:21:37.540 --> 00:21:39.360 Just a couple of words on, I guess, 380 00:21:39.380 --> 00:21:41.920 some of the other general uses that are growing. 381 00:21:42.320 --> 00:21:44.560 One is around things like power and data. 382 00:21:44.820 --> 00:21:49.120 So drones are getting very good at being able to go out 383 00:21:49.120 --> 00:21:51.140 and collect data sort of every day, 384 00:21:51.180 --> 00:21:54.560 instead of having patchy data around various things 385 00:21:54.560 --> 00:21:55.300 that are being looked at. 386 00:21:55.740 --> 00:21:57.180 Also things like sensors, 387 00:21:58.160 --> 00:22:00.480 lots of infrastructure has sensors, 388 00:22:00.580 --> 00:22:04.060 bridges, large roads, and they use batteries. 389 00:22:04.160 --> 00:22:05.160 So drones can be used to collect data, 390 00:22:05.180 --> 00:22:07.900 and now go out and recharge them wirelessly every day, 391 00:22:07.940 --> 00:22:09.900 if necessary, so that the batteries don't run out. 392 00:22:10.440 --> 00:22:13.000 We have things around coastal erosion 393 00:22:13.000 --> 00:22:14.840 and various things to do with the environment, 394 00:22:15.080 --> 00:22:17.840 whether it's a nest of orangutans or a coastline. 395 00:22:18.540 --> 00:22:20.580 And because it was very expensive, 396 00:22:20.740 --> 00:22:23.480 there's more and more, of course, 3D capacity to do drones, 397 00:22:23.620 --> 00:22:26.960 and there's now plans on the internet to be able to build them. 398 00:22:27.920 --> 00:22:31.820 There's things around the medical aspects 399 00:22:31.820 --> 00:22:33.520 of especially developing countries. 400 00:22:33.580 --> 00:22:35.120 So if we're studying something like tuberculosis, 401 00:22:35.960 --> 00:22:40.440