Mark Trotter
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09/25/2018
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26
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Mark Trotter talks about GPS for cows, fit-bits for sheep, laser beams in pastures, fenceless farms: An update on some of the latest agri-tech emerging in the Australian Grazing Industries.
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- [00:00:00.000](background chatter)
- [00:00:01.735]Well, Dr. Baden clapped
- [00:00:02.568]that means it's time to get started.
- [00:00:05.293]That had nothing to do with, Dr. Grable.
- [00:00:08.276](laughing)
- [00:00:09.550]Very much appreciate the attendance today.
- [00:00:12.530]I'm gonna invite, no stranger to many of you
- [00:00:16.637]but a stranger to some, back,
- [00:00:18.993]or welcome our colleague back
- [00:00:21.540]from Ohio State University to introduce our speaker.
- [00:00:25.310]Dr. Jim Kinder.
- [00:00:27.340]Some of you, like one of you way in the back row there,
- [00:00:30.140]knows Dr. Kinder very, very well
- [00:00:33.130]because he served as a major advisor.
- [00:00:36.034]Dr. Kinder came from Ohio State,
- [00:00:39.770]and through the ranks, from assistant
- [00:00:42.180]to associate to full professor
- [00:00:44.910]from 1979 to 1999 right here at the
- [00:00:48.710]Department of Animal Science at UNL.
- [00:00:51.174]He started when he was 12, okay.
- [00:00:52.899](laughing)
- [00:00:53.827]That's why he looks so young.
- [00:00:56.560]Dr. Kinder, then had the opportunity to go
- [00:00:59.451]back to Ohio State as department head,
- [00:01:02.132]served in that role for just under 12 years.
- [00:01:06.140]His leadership was obviously valued very highly,
- [00:01:10.611]and Dr. Baden who was there, can attest to that,
- [00:01:13.940]because Jim served in several interim roles,
- [00:01:17.930]in several different departments,
- [00:01:21.040]really through just, in the past year, right?
- [00:01:23.726]That would include Human Nutrition,
- [00:01:25.791]Physical Activity and Education,
- [00:01:29.185]and most recently at the Agricultural Technology Institute
- [00:01:32.900]at Ohio State University.
- [00:01:35.250]So, please help me welcome back Dr. Kinder
- [00:01:38.720]to introduce our speaker for today.
- [00:01:40.322](applause)
- [00:01:46.012]Well I appreciate that,
- [00:01:47.559]but what we're here for today
- [00:01:48.856]is this fellow to my left here.
- [00:01:52.220]What wasn't said is this University
- [00:01:55.750]supported me in traveling to Australia
- [00:01:58.390]in 1991-92,
- [00:02:01.780]and was there for a year, worked in the lab,
- [00:02:05.694]and went back about two years ago
- [00:02:10.814]for another year in Australia
- [00:02:13.770]and came across Dr. Mark Trotter.
- [00:02:17.200]Mark is off of a,
- [00:02:21.671]was born into a family that operated a dairy farm,
- [00:02:26.790]a Jersey farm, in New South Wales.
- [00:02:30.120]Australia only has seven states, by the way.
- [00:02:33.930]It's eight.
- [00:02:35.030]It's south of where he is now.
- [00:02:38.590]Eight.
- [00:02:39.818]Eighteen. Oh.
- [00:02:42.510]Anyway. (laughing)
- [00:02:44.869]And in that living, breathing farm,
- [00:02:48.290]that's where he got interested in
- [00:02:49.600]these precision technologies
- [00:02:51.780]that he's gonna talk to you about today.
- [00:02:55.416]We've been hosting him and his wife,
- [00:03:00.020]who also has a PhD in Agronomy,
- [00:03:02.040]that teaches in this program,
- [00:03:05.390]and now he's located at Central Queensland University,
- [00:03:09.230]and Ohio State has a memorandum of understanding
- [00:03:13.526]and Collaborations in various areas we're starting.
- [00:03:16.660]And he said when he came over here, he says,
- [00:03:18.900]I'd like to go to another University that you mentioned.
- [00:03:21.924]And I said, you need to go to Nebraska.
- [00:03:24.320]The college, he's in beef business now.
- [00:03:27.360]He's in beef capital of Australia,
- [00:03:29.275]and, so, that's the reason he's here today.
- [00:03:32.840]So, Mark, I'm just pleased as punch
- [00:03:35.920]to have you back in Big Red Country.
- [00:03:39.831]Thank you, Jim.
- [00:03:41.183](applause)
- [00:03:45.810]Righto, thanks.
- [00:03:47.095]I'm gonna give you guys sort of an intro.
- [00:03:49.662]Explain some of that stuff that you talk about.
- [00:03:52.175]And also we're gonna talk about Ag in Australia,
- [00:03:54.719]just to give you close view
- [00:03:55.674]before I run through any of that.
- [00:03:56.957]I'm gonna run through some of the technologies
- [00:03:58.960]that are emerging and being developed
- [00:04:00.462]in the Australian system and in the news stories as well.
- [00:04:06.023]Some helpful tips for listening to an Australian.
- [00:04:09.894]I talk too fast, I know that, I've already been told
- [00:04:12.460]I've got to space between every word.
- [00:04:17.096]But that's slightly in error.
- [00:04:19.520]If I'm going too fast for you, just stop me dead (mumbles).
- [00:04:25.207]And then some helpful definitions here.
- [00:04:28.280]So I'll talk in my, we have our own lingo, (mumbles).
- [00:04:31.530]And a producer or cocky, that's an agriculturist.
- [00:04:34.877]A grazier or pastoralist is a grazing animal producer.
- [00:04:38.254]I'll say paddock, you guys say field.
- [00:04:40.790]Feed-base, that's the pasture or forage.
- [00:04:43.922]A draft animal, you sort them.
- [00:04:47.082]We use a crush, you use a chute.
- [00:04:50.398]We have stockyards, you, you have
- [00:04:52.730]a handling facility or corral.
- [00:04:54.980]And mustering cows, we go, get out and round 'em up.
- [00:04:58.800]And a ute is a truck in your term.
- [00:05:03.230]And a strewth or crikey are expressions of surprise.
- [00:05:07.630]So that's what it is.
- [00:05:10.683]So moving on back, we all know I grew up on this dairy farm,
- [00:05:13.070]on the Mid-North Coast of New South Wales.
- [00:05:15.101]About halfway between Sydney and Brisbane.
- [00:05:17.710]Spent a lot of time on my grandfather's
- [00:05:19.527]beef operations as well.
- [00:05:21.830]Spent a lot of time riding horses and camp drafting.
- [00:05:23.793]Does anybody know what camp drafting is?
- [00:05:26.225]Nothing in the US (static) like it.
- [00:05:28.932]No, it's a little bit like cross between
- [00:05:30.468]cutting, team penning and a barrel race.
- [00:05:33.079]You kinda come out and then you call a gate,
- [00:05:35.651]you run up to a football field,
- [00:05:36.700]then you gotta chase a cow around this little,
- [00:05:38.860]uh, barrels and it's a big business in Australia.
- [00:05:43.168]So, I went to University of New England.
- [00:05:46.230]Got a Bachelor of Rural Science.
- [00:05:48.020]I was gonna become a banker because I wanted
- [00:05:50.096]to learn a little bit more about finance,
- [00:05:52.409]and how I was to make money.
- [00:05:54.857]Then I got that PhD at UNE.
- [00:05:57.410]Then I saw what the cropping world was doing,
- [00:06:00.553]research in agriculture, I thought we could
- [00:06:02.038]do some of that in grazing and got really engaged in that.
- [00:06:05.734]Moved up to CQ Uni about two years ago,
- [00:06:09.981]I went to Queensland.
- [00:06:12.626]That university is a relative baby, compared to you guys,
- [00:06:15.863]so we've only been around since 1967.
- [00:06:18.781]We have a lot of campuses across Australia,
- [00:06:20.990]but we're headquartered in Rockhampton,
- [00:06:23.389]and we have a relatively strong track record
- [00:06:26.060]in research and in beef, in particular.
- [00:06:30.452]A big focus on making a difference in our community.
- [00:06:33.201]So effecting real change.
- [00:06:35.347]I'm based at CQIRP, which is my research center, my office.
- [00:06:39.420]Then we go up (mumbles).
- [00:06:44.800]And then if you wanna go somewhere bigger,
- [00:06:47.435]like to the bigger, the Belmont Station just along town.
- [00:06:53.373]You can see the river running around, the property there,
- [00:06:56.724]that's all a part of us and we have two classes in there,
- [00:07:00.353]in like a big house..
- [00:07:02.610]We also have these things with our sheep
- [00:07:05.005]right here at Longreach, as well.
- [00:07:07.450]Give you a background on the beef industry
- [00:07:09.899]here in Australia, if you don't know anything about it.
- [00:07:11.927]Rainfall drives production across the country.
- [00:07:15.103]Probably know they are a very dry continent.
- [00:07:17.778]There's more rainfall around these coastal areas,
- [00:07:21.279]than the southern areas.
- [00:07:23.600]And you get reasonable rain farther north.
- [00:07:25.643]But there's a big division between north and south.
- [00:07:29.090]Down here we have our reasonable rainfall dominant area,
- [00:07:33.814]and as you go through the north it builds,
- [00:07:36.867]almost like a monster and the taxes,
- [00:07:38.307]where you got a really wet summers and very dry winters.
- [00:07:43.427]And that influences how we grow right
- [00:07:45.918]across Australia, actually.
- [00:07:49.252]Our beef industry, we have about
- [00:07:51.297]50 thousand base properties,
- [00:07:54.120]25 million head of cattle,
- [00:07:55.757]and a breeding heard about 11 million.
- [00:07:57.160]So that's not that big compared to some
- [00:07:59.630]of the bigger guys out there like you guys in the field.
- [00:08:03.640]One thing that's done with ours is we finish
- [00:08:05.963]a lot of our cattle on the pasture.
- [00:08:08.826]So only 40% are grain finished.
- [00:08:11.283]60% of them go straight off the pasture,
- [00:08:12.116]through the kill corral and then onto market.
- [00:08:17.683]So this is where I am.
- [00:08:19.864]We are, we have, we see the biggest, I guess,
- [00:08:23.660]county of all stock in all Australia.
- [00:08:26.200]We have the most number of animals
- [00:08:28.678]and we're somewhere in the middle of them.
- [00:08:32.380]In the Northern Beef Industry, a little bit I told
- [00:08:34.821]you about the Southern and Northern divide.
- [00:08:37.060]That Southern Industry, there's a lot of tourist capital,
- [00:08:39.833](mumbles) and as you get up to this Northern Industry,
- [00:08:44.028]this is the real cowboy country,
- [00:08:46.580]so only the (mumbles) animals and strong and tough animals,
- [00:08:49.373]are the only ones that will survive up there.
- [00:08:51.700]And even, quite extensive property, really nice areas,
- [00:08:56.050]millions of cattle heads in just one company,
- [00:08:58.897]and you actually get a property that (mumbles) of cattle.
- [00:09:02.919]So you don't round 'em up.
- [00:09:04.513]You usually go out with a pull catcher,
- [00:09:06.483]just pull these straight to you and they go on up
- [00:09:10.470]and he comes out, sees that bull and he pulls him over,
- [00:09:14.593]and puts a strap on his back legs
- [00:09:16.095]and drags him up onto the truck itself.
- [00:09:17.457]So it's a pretty wild country out there.
- [00:09:20.965]Uh, a lot of opportunity to improve the management
- [00:09:24.293]of this sort of practices that are out there
- [00:09:26.489]because I've been on that boat now a little while.
- [00:09:29.929]So that's where I'm working and doing the research
- [00:09:32.428]that will try to make change up there.
- [00:09:35.813]Okay, we need a little something in the Agritech
- [00:09:37.953]that we're working on in this industry.
- [00:09:39.780]Uh, but just before then,
- [00:09:40.970]this is the research team that we have at the moment.
- [00:09:45.362]I have previously worked with
- [00:09:46.195]a whole bunch of people up at UNE,
- [00:09:48.290]University of New England and University of Wales.
- [00:09:51.530]And so all of this work is just
- [00:09:54.079]mainly a whole bunch of people
- [00:09:55.577]behind the scenes to make all of this happen.
- [00:09:58.810]Okay, so laser beams in pastures.
- [00:10:00.740]So why are we doing that?
- [00:10:02.720]Measuring the amount of grass we have on ground
- [00:10:05.516]is really what practices they may have, I mean
- [00:10:07.968]your grains per hectacre and by
- [00:10:11.224]the recurring biomass, the biomass
- [00:10:14.653]to make the measurements decisions
- [00:10:16.722]to rotate livestock and all that.
- [00:10:19.807]And we've been working on a number of platforms
- [00:10:21.876]over the years now.
- [00:10:23.791]We've got systems that use satellite
- [00:10:25.650]to estimate the amount of biomass on the ground.
- [00:10:28.772]And there are satellite systems
- [00:10:30.975]like this Pastures from Space
- [00:10:32.834]and Rangewatch, some of the normal systems
- [00:10:35.765]and I helped produce many of those talking device
- [00:10:38.964]to optimize and actually not over graze it
- [00:10:42.948]and reduce the grain of.
- [00:10:45.010]I've done some work with working around with
- [00:10:47.144]active optical sensors.
- [00:10:49.500]Some of the original work that I've done out in UNE
- [00:10:51.876]is the growing part in academical senses.
- [00:10:54.673]Egypt, all of the organization staff point
- [00:10:57.642]in the first place and then in particular
- [00:10:59.960]sensors that's in the device on the ground
- [00:11:02.297]and developing any crowd sourced apps
- [00:11:05.209]that allows us to tell when that system
- [00:11:07.182]is more effective with.
- [00:11:09.462]We recently started using laser sensors
- [00:11:12.565]in the same context to improve the accuracy
- [00:11:15.209]and make these things a lot more reliable
- [00:11:18.197]in terms of the data that providing that produces.
- [00:11:22.489]Not only on that, we are currently coming out with
- [00:11:25.286](mumbling)
- [00:11:32.048]So the future in this space with the work
- [00:11:33.983]having UAVs, ground robotics, they're out there.
- [00:11:37.450]Graduate into Radar satellites.
- [00:11:39.768]A whole new generation of satellites helping us
- [00:11:42.440]taking measurements while other sensors on the ground
- [00:11:44.960]help our producers optimize the software.
- [00:11:49.820]GPS on cows?
- [00:11:52.350]This is the evolution of GPS in terms of tracking animals.
- [00:11:56.910]The world behind this sort of technology has been
- [00:11:59.673]on the ears, right?
- [00:12:01.243]So they been tracking the mountain lion
- [00:12:03.695]or the bear or the elephant
- [00:12:06.033]and they're able to do that because
- [00:12:08.389]they can afford to put a small number
- [00:12:10.390]of devices on relatively high number of animals.
- [00:12:13.513]When it comes to livestock, it's the complete opposite.
- [00:12:16.770]You want to have as many post together as we can.
- [00:12:18.850]And so thinking in sort of in terms of cows
- [00:12:23.025](mumbling)
- [00:12:30.228]And we've been developing this through
- [00:12:33.670]simple store-on-board collars and on their ears
- [00:12:36.895]to best provide a lot of devices
- [00:12:38.820]that track the whole herd from home.
- [00:12:41.512]And what's happening now is that
- [00:12:44.672]it's gonna shift from just researchers using it
- [00:12:48.710]to tools being developed so producers can use it.
- [00:12:52.105]And so in each app systems it produces
- [00:12:55.113]an ear tag and a collar most the time
- [00:12:58.887]and we're actually getting in real time data delivery.
- [00:13:00.990]So they sit back here,
- [00:13:02.780]look to see where the cows are moving.
- [00:13:05.827]Location for us is really important in Australia
- [00:13:08.930]in a lot of new context.
- [00:13:11.300]There are technologies out there
- [00:13:13.006]that can track live animals in the barn
- [00:13:15.362]on an ESP type system but in Australia
- [00:13:18.120]we are dealing with humanitarianism in terms of grazing,
- [00:13:21.630]so we need to know where they are and what they're doing.
- [00:13:24.690]And also where are they if we need
- [00:13:26.722]to go find them and treat them.
- [00:13:28.676]And so location of GPS from space
- [00:13:30.543]has been working really well.
- [00:13:35.726]This, one of the really interesting things
- [00:13:38.330]that the GPS tracking in a lot of sense
- [00:13:40.223]allowed us to do with really much closer
- [00:13:43.906]understanding of how our animals behave,
- [00:13:46.350]what they're doing.
- [00:13:48.983]So once upon a time where we would have
- [00:13:50.937]had to stand with them we might have had 20 cattle.
- [00:13:53.080]We use to follow them after everyday
- [00:13:56.186]and you can see the that the cow
- [00:13:58.200]that was fist alone suddenly start to draw back in order
- [00:14:00.610]and he'd say there's something wrong with that cow.
- [00:14:03.465]What's going on?
- [00:14:05.150]In the other book he incurs like 1000, 2000 animals.
- [00:14:09.481]There's just no time for us in the world today generally.
- [00:14:13.121]And the same in the food industry.
- [00:14:15.400]So a sensor based approach is really
- [00:14:18.063]giving you the opportunity to bring back
- [00:14:20.956]that idea of individually watching the animal
- [00:14:23.657]but being all remotely.
- [00:14:25.534]So if we can, I believe if we combine
- [00:14:27.948]good animal management and good knowledge
- [00:14:30.534]the better we can capture symptoms with these sensors
- [00:14:33.504]we actually start to improve our work productivity
- [00:14:37.316]and work outcomes for our animals.
- [00:14:39.634]Also, there's the researchers,
- [00:14:41.626]any of you guys have been out watching
- [00:14:45.017]all of these information studies,
- [00:14:47.527]but it can get pretty tiring
- [00:14:49.002]sitting out there days on end and nights on end.
- [00:14:51.580]And this sort of technology, in some ways
- [00:14:53.740]taking away from the ability to do that sort of work.
- [00:14:58.868]So if you look at it at a commercial context
- [00:15:01.320]how is it producing what it produces.
- [00:15:03.200]Grazing just did an interesting survey a little while ago
- [00:15:07.120]and they came up with a
- [00:15:08.868]massive list of different applications.
- [00:15:10.879]We can view this information remotely
- [00:15:12.470]and in realtime but that won't be till Fall.
- [00:15:15.850]Not surprisingly for Australia
- [00:15:18.440]more related payments are being issued
- [00:15:20.240]so producers want to know that they're in
- [00:15:23.159]optimal water to have to drink
- [00:15:25.170]because we can perish animals,
- [00:15:27.240]degradation is dirty in that situation
- [00:15:29.830]so having a sensor to take that drinking behavior
- [00:15:32.960]is quite important.
- [00:15:34.864]You can see it in the full range
- [00:15:36.262]in the applications that they're interested in doing.
- [00:15:39.864]And so really simple stuff, so we have animals.
- [00:15:43.944]Are they on the farm or have they made it to town?
- [00:15:47.335]Or are they looking for companion?
- [00:15:50.100]So the other simple sort of applications
- [00:15:53.670]protecting stock theft.
- [00:15:56.320]So we've got cattle wrapping.
- [00:15:58.695]I don't remember where, established
- [00:16:00.898]from like the whole nation of convicts
- [00:16:03.484]of English settlement.
- [00:16:04.615](laughing)
- [00:16:05.448]Suspecting the timing for those attributes.
- [00:16:07.833]So stock theft conservatively costs
- [00:16:10.515]67 million dollars a year in the industry.
- [00:16:12.756]Let's say what we're doing tending
- [00:16:15.140]they stopped thefts as they're happening
- [00:16:17.756]and we have the technology to do that.
- [00:16:20.550]Says a little bit about the GPS stock with cattle
- [00:16:24.060]who actually meandering happily
- [00:16:27.060]down to the campsite, to the resting site.
- [00:16:30.330]That's quite torturous way to move
- [00:16:33.140]and then what's happened is I put in a behind
- [00:16:34.825]a simulated target that pushed it back to the yard
- [00:16:38.230]and you can see you can patent this method
- [00:16:41.492]but using the tracking devices to pick up
- [00:16:44.280]those changes in behavior, ultimately to hopefully send
- [00:16:48.560]the text message to the farmer.
- [00:16:51.071]And if he's at the coffee shop
- [00:16:52.680]he can now find out that somebody's stealing his cows.
- [00:16:55.590]So he might not care about a sharp
- [00:16:57.680]level conversation and a glass of wine.
- [00:17:00.151](laughing)
- [00:17:02.469]Landscape utilization.
- [00:17:04.002]This is something not particularly
- [00:17:06.473]to the path of most of you but for actual sustainability.
- [00:17:09.902]So animals do not graze out grasslands evenly.
- [00:17:14.212]They prefer the certain areas.
- [00:17:15.760]You see the shapes on the top of this hill
- [00:17:19.346]that cows have their flats
- [00:17:20.860]and they show up in the image.
- [00:17:22.803]This is some sheep tracking data
- [00:17:25.208]and this is the sheep going east and then north.
- [00:17:28.772]It's not really rocket science.
- [00:17:30.323]They spend a lot of time up there.
- [00:17:32.239]They move into the first meadow at the top
- [00:17:34.480]and really high levels of phosphorus.
- [00:17:37.277]Alright, so the sheep are grazing
- [00:17:39.404]off these flats during the day
- [00:17:42.067]and then they go off to the tops of the hills and camp
- [00:17:44.193]and they're exporting nutrients
- [00:17:46.051]up to the tops of those hills all the time.
- [00:17:48.848]And so if we can, I guess, objectively measure this
- [00:17:52.201]sort of nutrient variation over time
- [00:17:54.691]we can actually start to think about
- [00:17:56.683]changing the way we put fertilizer out.
- [00:17:59.480]So another way we can put fertilizer out
- [00:18:01.664]on top of this whole hill at the same rate,
- [00:18:04.557]exactly what the property owners are doing currently.
- [00:18:07.335]They're putting their fertilizer down here
- [00:18:09.576]and we've actually got other companies now
- [00:18:11.549]developing that sort of systems for incorporating operation.
- [00:18:17.086]What else could we do with GPS monitoring?
- [00:18:19.883]Some of the other stuff that we look at
- [00:18:21.377]are detecting calving and lambing activity.
- [00:18:24.787]And so we measure a range of attributes
- [00:18:27.814]that the day, the speed, then drops off
- [00:18:30.917]just like we have in there
- [00:18:32.737]and then change stage while that lambing
- [00:18:34.883]for us to save it if we could.
- [00:18:36.971]All the way to the social attribute
- [00:18:39.078]to capitalize on like to be friends.
- [00:18:41.243]So that you or somebody else can actually
- [00:18:43.005]snakes off and calving and lambing.
- [00:18:45.706]So ultimately again, a text message
- [00:18:48.216]is produced to say that this cow
- [00:18:50.534]or this q has gone off and have
- [00:18:52.775]it cast in assist at all?
- [00:18:54.250]Or if there's a problem the text message
- [00:18:55.898]could say, hey, there's a safety going on
- [00:18:58.791]you need to get out and check that thing out.
- [00:19:01.511]Predation events.
- [00:19:02.948]We have a lot of dingos in Australia
- [00:19:05.783]and so we see an enormous number
- [00:19:08.044]of particularly sheep and also cow
- [00:19:10.074]in most of Australia to ward those attacks.
- [00:19:12.584]So we're working on projects at the moment
- [00:19:14.614]to detect that dog attack event.
- [00:19:16.588]It's not rocket science.
- [00:19:18.197]When sheep get attacked by a dog
- [00:19:19.940]that's amongst the class of we normally would.
- [00:19:22.699]But everything else is sort of natural sometimes.
- [00:19:27.280]They're either trying to protect
- [00:19:29.001]or work in a way not really to produce
- [00:19:31.683]the information about the wilderness.
- [00:19:34.423]When sheep start to get attacked by other dogs
- [00:19:38.120]and you come back and start stealing
- [00:19:40.460]and what's happening is (mumbling)
- [00:19:45.879]spun out to the outside and the dogs come in
- [00:19:48.216]to get them all and take them down.
- [00:19:49.300]They're trying to detect those behaviors
- [00:19:51.741]as well as providing an alert to the producer.
- [00:19:55.074]There are some really interesting things,
- [00:19:56.779]I've just done some little pilots
- [00:19:58.350]showing how much producers across Australia
- [00:19:59.950]need different applications of this.
- [00:20:02.469]And one of them came out of where I was speaking
- [00:20:05.055]was the relationship between things like
- [00:20:08.618]calf characteristics and this is just
- [00:20:12.250]the animals that are traveling in the path confines.
- [00:20:15.000]They say that the number of animals is
- [00:20:17.699]fairly extremely less.
- [00:20:19.078]Any software being developed by any stretch is elemental
- [00:20:21.377]but it really adds a lot to the amount
- [00:20:23.413]of that you made something in this.
- [00:20:26.090]You know, can we start to detect the relationship
- [00:20:30.400]between how my animals are moving and grazing
- [00:20:32.660]than the cutting well before they are on the kill floor.
- [00:20:37.066]The animals can show symptoms that they gonna end up dying.
- [00:20:41.128]You know the production system way really up
- [00:20:44.365]in terms of broader not spend all our money
- [00:20:47.296](mumbling)
- [00:20:50.898]There's a recent column in the next slide as well.
- [00:20:54.921]They been in this area for about 10 to 15 years
- [00:20:59.820]and there's more coming now ever in terms of
- [00:21:01.960]commercialization of developing GPS tracking
- [00:21:05.457]tags for the industry so that's quite exciting.
- [00:21:08.714]And there's now an opportunity for you guys
- [00:21:10.879]to pick up a rep if you're a student.
- [00:21:13.388]In these numbers they are all here.
- [00:21:17.239]But you guys would be understanding
- [00:21:18.714]that would be all the signs and what have you.
- [00:21:22.143]Alright, fit-bits for sheep.
- [00:21:23.541]How does this work?
- [00:21:24.461]You guys all been going with your fit-bit sensor.
- [00:21:27.277]It works off an accelerometer.
- [00:21:29.090]It's just a motion sensor
- [00:21:31.400]and that measures the movement moved
- [00:21:34.806]within these three axis.
- [00:21:37.040]You guys can get get a trice on the ace and ones, yeah?
- [00:21:41.630]I mean you can see that the differences
- [00:21:42.990]highly stand out quite well.
- [00:21:44.863]With standing it's quite still.
- [00:21:47.315]Walking, you almost see the steps.
- [00:21:49.806]Grazing, a step, step, a bite, a step, step, a bite.
- [00:21:54.020]And then lying down.
- [00:21:54.970]And so we can see the really
- [00:21:59.380]fine scale change in that activity.
- [00:22:06.617]In a research context we used these sensors
- [00:22:09.942]to determine a calf it would come six months
- [00:22:13.280]to quantify things like how much time
- [00:22:15.090]it has been sucked from the cow.
- [00:22:17.968]Developing hormones, that's quite important
- [00:22:21.340]because in northern Australia
- [00:22:23.470]we usually lose anywhere up to 20% of our cows.
- [00:22:26.704]We are seasoned.
- [00:22:28.543]We actually don't really know the complete reasons
- [00:22:31.530]why is this, in all these sensors.
- [00:22:33.570]So we can't understand cow in terms of this.
- [00:22:38.083]For commercial producers there are a range
- [00:22:41.263]of different applications in terms of
- [00:22:43.121]getting our full numbers higher.
- [00:22:44.690]But one of the big ones for us is the disease detection.
- [00:22:47.100]I know not everyone is well fed.
- [00:22:49.156]So far we ran ours with fly tags
- [00:22:51.800]like chemical air tag and buffalo fly.
- [00:22:55.710]The biggest thing of your own platform
- [00:22:58.524]there are all sorts of insects that comes around
- [00:23:01.780]and one of the finishes we have
- [00:23:05.382]is that we wanted to lighten these tags up
- [00:23:07.340]as well as possible
- [00:23:09.520]in order to last the whole life of the season.
- [00:23:10.980]But there's a threshold which we may be here now.
- [00:23:14.252]Over production is an issue and
- [00:23:16.455]then you don't know what sort of concerns
- [00:23:18.830](mumbling)
- [00:23:23.409]So we've been using the same accelerometer ear tag sensors
- [00:23:27.738]to actually detect these changes in behavior over time.
- [00:23:31.723]It's not rocket science.
- [00:23:32.556]You can see this cow here who are equipped with
- [00:23:35.439]and see this cow over here, she's throwing her ear around.
- [00:23:39.347]She's trying to get the flies off
- [00:23:40.823]and they're beating the flies off of themselves
- [00:23:42.477]and you pick that up with that accelerometer really easily
- [00:23:46.490]because of the rapid movement of that node.
- [00:23:49.127]And so what we're able to do is
- [00:23:51.780]get to a result that is relatively simple.
- [00:23:53.983]That's fly agitation index.
- [00:23:56.263]So what you can see here on the bottom
- [00:23:57.867]that's the cow that have controlled ear tag.
- [00:24:01.050]You notice she wasn't being bothered by flies at all?
- [00:24:04.386]Where in this one in here was that
- [00:24:06.780]animal that didn't have a chemical control ear tag.
- [00:24:10.290]So you can see how over time what's happening to these.
- [00:24:13.370]These flies and where it was the worst.
- [00:24:15.360]When she had the problem to work out
- [00:24:17.891]cause we couldn't keep her and let her be control anymore.
- [00:24:21.270]And as soon as that thing came off it crashed back down.
- [00:24:24.660]So it seems really be picking up.
- [00:24:26.830]And now what we're working on is
- [00:24:28.070]getting help on the producers ear piece
- [00:24:31.470]to provide a moving where they have those tags now.
- [00:24:36.560]One of the other issue with both Australia
- [00:24:39.003]and animal welfare.
- [00:24:40.550]It is a social crisis issue
- [00:24:43.030]and the NI of Australia, it's a potential
- [00:24:46.600]three billion dollar downside risk to our industry.
- [00:24:50.260]So if we lose agricultural license
- [00:24:53.120]then we'll lose a lot of money.
- [00:24:55.037]The other sides of tech that are being developed,
- [00:24:57.600]we have sort of the title package of the
- [00:24:59.880]objective welfare division with each operator
- [00:25:05.544]sort of late markets (mumbling)
- [00:25:12.053]to shaking and moving their sensors
- [00:25:14.788]to be able to tell through their instruments
- [00:25:16.914]that look, it's shaking.
- [00:25:17.917]It has been in this state for five,
- [00:25:21.844]some real productions in that space.
- [00:25:25.178]So last thing we are going to research today.
- [00:25:29.380]The theory institutes had a number of devices
- [00:25:31.480]over the last few years.
- [00:25:33.396]Things like the smart phone (mumbling)
- [00:25:42.746]Meat can be developed in Texas.
- [00:25:45.293]But primarily dairy is the most free money to students
- [00:25:49.028]which is what we timed, and we need something
- [00:25:51.423]that will work past the areas where
- [00:25:54.354]we need the radius right from the tag
- [00:25:59.584]or all the way back to the cloud.
- [00:26:03.185]So social network for cows.
- [00:26:06.193]And this is a really interesting one.
- [00:26:08.740]What would we do is use these proximity loggers.
- [00:26:11.610]So if the device goes to another animal collar,
- [00:26:14.017]and it tells you how much time each cow
- [00:26:16.820]actually speak together over the day,
- [00:26:19.370]over the week or over the month.
- [00:26:20.980]And from that you can basically use
- [00:26:23.320]the exact same sort of element
- [00:26:26.010]that Facebook account using against you does.
- [00:26:28.040]Or you first want to think about it
- [00:26:32.160]to understand the relationships between two animals.
- [00:26:36.280]So what we're looking at is a depth finding
- [00:26:38.997]automated which cow matches which cow.
- [00:26:42.440]It's not rocket science.
- [00:26:44.290]Just not something unusual to
- [00:26:46.266]know the pedigree of each animal.
- [00:26:47.290]We use to do it in the yards.
- [00:26:49.130]We also use to get quite warm in the yards.
- [00:26:51.503]And by having a way of doing that
- [00:26:53.550]you can actually err out which cow
- [00:26:56.273]belongs to which calf because
- [00:26:57.880]it's been a long time together over a day
- [00:27:01.251]over a week, or over a month.
- [00:27:03.215]And so there's also other really interesting
- [00:27:06.454]applications of this in looking at the
- [00:27:08.540]social structures of the herds.
- [00:27:11.187]Having a matriarch, mother metric, leading metric,
- [00:27:15.420]showing they have a high, as we define model.
- [00:27:21.877]This is a little spin off of our university.
- [00:27:27.053]This is the Ani-sense Project.
- [00:27:30.770]This mode was pitched to you guys.
- [00:27:33.700]We're trying to develop a platform
- [00:27:35.520]that you can, just a platform that will
- [00:27:38.598]measure a range of different things.
- [00:27:43.154]So we talked about accelerometer and proximity.
- [00:27:46.936]We're also exploring heart rate of the ear.
- [00:27:50.060]These already on these.
- [00:27:52.349]And any of that in realtime.
- [00:27:55.160]This is a research platform and
- [00:27:57.323]even to a commercial platform, some researchers.
- [00:28:01.461]And so we went way around to other universities
- [00:28:05.787]engaged in this world.
- [00:28:09.632]Okay, so where are we at now?
- [00:28:11.580]Today we've talked about having lots of animals
- [00:28:14.752]and having lots of property.
- [00:28:16.760]Now we're moving to actually how to manage them.
- [00:28:19.371]So there's this concept of virtual fencing.
- [00:28:21.732]Mostly does what the dog containment systems
- [00:28:25.034]where you got a electrical device on the collar.
- [00:28:27.420]You bury in the ground your wire.
- [00:28:29.360]Your dog comes up to that place,
- [00:28:31.325]it gets a beep, then if it tries
- [00:28:32.767]to go over it gets a zap.
- [00:28:33.790]There was some of those instances where
- [00:28:35.440]pretty much the same as that but
- [00:28:37.400]it's all GPS controlled.
- [00:28:39.550]So you don't have the ground wire.
- [00:28:41.314]It will know if it moves around the parameter.
- [00:28:44.010]This is where it started.
- [00:28:45.630]Somebody stuck a computer on a poor cow's head.
- [00:28:48.461]And it eventually got downsized.
- [00:28:52.340]And this is a commercial solution truth be told.
- [00:28:56.173]It doesn't mean it's actually working.
- [00:28:58.284]But this is how it works on sheep.
- [00:29:00.144]I understand you are an eight while the students
- [00:29:05.442]Here's the invisible fence.
- [00:29:06.905]It does show red for the color.
- [00:29:08.780]It's one of the beep methods,
- [00:29:12.060]and they're walking up to that fence
- [00:29:13.780]actually then got a beep.
- [00:29:15.800]And then she gets another beep beep.
- [00:29:18.210]This is the first time the sheep's seen this place.
- [00:29:21.830]And then she get a loud beep
- [00:29:23.853]and wondering what's going on,
- [00:29:25.003]she ignored it, she gets zapped.
- [00:29:27.469]Important not is that sheep are not
- [00:29:29.538]as silly or dumb as people would have you believe.
- [00:29:33.840]So within about three hours
- [00:29:36.030]we had that little flock grazing up and down
- [00:29:38.336]that invisible fence quite happily and
- [00:29:40.676]responding to the audio signal and
- [00:29:43.414]not getting the resources that within the safe zone.
- [00:29:46.904]Here's some of the work we did for Agersens.
- [00:29:51.670]This is just a little throw away
- [00:29:53.210]where we are testing the feast with these devices on
- [00:29:56.079]whilst eating this, and the cows are angus
- [00:29:59.025]and carabous types.
- [00:30:00.509]These had a slightly different neck shape
- [00:30:02.954]and we wanted to see whether we could
- [00:30:04.668]get them to feed on grass with it.
- [00:30:07.092]But you can you see here these guys
- [00:30:08.848]are sort of back bone kind of animals
- [00:30:11.063]and there's a bit of a concern around
- [00:30:13.571]having devices on animals that will
- [00:30:15.681]keep them at their electrical stimulus
- [00:30:18.127]but overall I've seen would suggest that
- [00:30:20.810]they always really quickly learn to respond to the audio.
- [00:30:24.820]And the dynamic of the herd, they go back to the herd
- [00:30:27.614]and so it's a really good management tool.
- [00:30:30.540]A great opportunity to revolutionize the way we
- [00:30:33.591]graze our landscapes, keep animals off sensitive
- [00:30:36.450]rough areas where we gotta put soil, empty rivers and such.
- [00:30:41.887]And again these are our commercial providers
- [00:30:44.630]in this space, Agersens I already said.
- [00:30:47.531]Vence from over east of us and
- [00:30:49.286]Halter from New Zealand.
- [00:30:51.376]Again, it's really opportunities to utilize
- [00:30:53.466]to working in this user case cause
- [00:30:56.380]they constantly employ digital space and,
- [00:30:58.607]The deal with the cloud.
- [00:31:01.990]How do we get all this information from
- [00:31:04.626]the account to the cloud, cloud server.
- [00:31:07.990]And from the cloud server, back to the
- [00:31:09.955]producer, the server to saddle.
- [00:31:11.773]And that's (mumbling)
- [00:31:19.025]Another new technology, walk-over-weigh.
- [00:31:24.124]We already have walk-over-weigh stations
- [00:31:26.193]that were built out of pallets.
- [00:31:29.474]So we basically get a lot of that gain
- [00:31:31.815]on a little different day rather than
- [00:31:33.695]the central animal cells.
- [00:31:36.538]And what would we do with this?
- [00:31:38.473]Using a really simple chip in computers
- [00:31:41.846]or a device, and send it out based on the type
- [00:31:44.730]and get back to the server and then
- [00:31:50.247]turn around and give it back to our producer
- [00:31:53.382]to utilize that data and develop a system of data
- [00:31:57.770]and a visualization platform for
- [00:32:00.800]producers to see this information.
- [00:32:03.789]So I want to go over here and I can see
- [00:32:06.130]that my wildlife game, and this is a
- [00:32:07.960]screenshot taken a couple days ago.
- [00:32:11.793]It's actually coming down in by the last of August.
- [00:32:14.092]So that's been wired for me.
- [00:32:15.680]So just try to get south of that there
- [00:32:18.564]to make sure we try and reverse it
- [00:32:20.300]to take out a better cow.
- [00:32:22.460]That we can all see at the moment.
- [00:32:26.109]So none of the most wooded data
- [00:32:29.923]would like to sense data from those charts
- [00:32:34.210]to really new generation of these systems
- [00:32:36.997]from GPS and accelerometer in the future.
- [00:32:41.302]Okay, that's sort of some of the tech I guess
- [00:32:45.710]that we're working on in moving the industry.
- [00:32:49.410]Just one thing I want to talk about is
- [00:32:51.800]in Australia we have a really key issue
- [00:32:55.170]in engaging young people into agriculture.
- [00:32:58.481]I see a lot of you guys out there.
- [00:32:59.930]We're gonna be the future of agriculture which is fantastic
- [00:33:03.300]but we just don't have young people coming
- [00:33:06.070]in to add to the industry now.
- [00:33:08.825]And so whenever you try to engaging kids at random
- [00:33:12.350]for that doing anything in that,
- [00:33:15.471]they should consider it as actually a career.
- [00:33:18.794]So another thing is active learning modules.
- [00:33:22.974]So there's GPScows, Pastures from Space
- [00:33:26.697]and Active Ewe maths curriculum
- [00:33:29.570]and these in this technologies
- [00:33:31.876]with GPS tracking and all the schools.
- [00:33:34.760]The kids in high school, they can track and read cows
- [00:33:37.270]and see the farmers cows, looking at data
- [00:33:39.707]exploring returning data you know.
- [00:33:42.639]Anything is possible isn't just about any hall.
- [00:33:45.150]That's what they thought it was previously.
- [00:33:47.237]It was actually a work of many technology
- [00:33:48.650]being used to,
- [00:33:51.082]And by the way, having those parts right here
- [00:33:53.653]they were already made, already stayed round here.
- [00:33:55.951]So they are the schools.
- [00:34:01.113]Alright.
- [00:34:02.430]So the last thing I want to finish on
- [00:34:05.836]is maybe an invitation.
- [00:34:07.920]You must have university to come over.
- [00:34:09.810]You're way to different capacities.
- [00:34:13.600]Some pretty big things to come and see.
- [00:34:16.640]It's not all hard work.
- [00:34:18.320]We need the hard work but we need the
- [00:34:22.785]more exceptionally the beef capital of Australia
- [00:34:25.209]every three years we do Beef Week
- [00:34:28.344]where we have about 100 guests come through the gates.
- [00:34:33.025]The next one is in 2021.
- [00:34:35.199]So you got that ahead of you or
- [00:34:37.372]if you know anybody that would be interested.
- [00:34:38.760]We also have fun, spending time at the rodeo,
- [00:34:43.621]the only way area inside the hotel, the bar.
- [00:34:46.730]So you have it here, and they arrive
- [00:34:50.308]and they practice every Wednesday and Friday nights.
- [00:34:54.802]And that's with most hotel and driver.
- [00:34:57.184]We also handle the hike for boating.
- [00:35:01.113]The key spice is the Barra which is the best
- [00:35:03.495]sport fly fishing in Australia.
- [00:35:06.714]And we also have some things to add to that
- [00:35:09.389]if I come across I will bring it up.
- [00:35:11.750]And right on the way is the Queensland coastline
- [00:35:17.100]which is what we address.
- [00:35:19.712]Getting home is about half an hour to pipeline
- [00:35:23.704]and further east to the Great Barrier Reef.
- [00:35:27.194]Basically just move the snow off the rake at the bottom.
- [00:35:32.920]So all these will be the pan handle to arrive.
- [00:35:38.692]There's a bunch of opportunities.
- [00:35:40.368]If you're a student, we got coming up
- [00:35:42.305]some Summer internships, post-graduate opportunities,
- [00:35:47.509]we have a PhD program obviously
- [00:35:49.662]but we've also got a good part time PhD
- [00:35:52.002]in Australia through the Fulbright organization.
- [00:35:55.910]And post-doctoral opportunities
- [00:35:59.965]throughout Advance Queensland.
- [00:36:03.120]There are some research fellowships
- [00:36:04.420]that we can set you up with.
- [00:36:06.350]And if you're rowdy we got some of
- [00:36:10.017]the Sabbatical county investigative
- [00:36:12.044]in a summary a bit strong.
- [00:36:14.176]It's something through Australia
- [00:36:17.540]we will find out more on the salary on that.
- [00:36:20.194]We also sponsor Fulbright scholarship,
- [00:36:22.430]the University does.
- [00:36:24.395]It makes a thing every year.
- [00:36:27.028]And today, helping one more person this year.
- [00:36:33.904]That's what the key opportunities.
- [00:36:40.510]So if you see anything you really like
- [00:36:43.768]come look at me I'll give you my card.
- [00:36:46.673]Otherwise, thank you for your time.
- [00:36:48.679](applauding)
- [00:36:59.045]Question on the GPS that challenges me.
- [00:37:04.750]We're using the GPS with the old school methods.
- [00:37:08.930]What's the cost of some of those tags
- [00:37:12.524]and view drades and interval for battery life and so on?
- [00:37:17.331]There's no commercially available e-tag
- [00:37:21.980]yet you can get them online to hold GPS.
- [00:37:25.817]Now it's probably familiar but there's one company
- [00:37:29.317]that's doing calls at the moment.
- [00:37:33.694]Which last time I looked were produced in Mexico.
- [00:37:36.474]In terms of the green light, the system that
- [00:37:40.236]we were just gonna research on a commercial platform
- [00:37:44.980]we were able to maintain a sample
- [00:37:47.278]and keep it about one every ten minutes.
- [00:37:50.225]So GPS, cause you allow GPS to choose what objects
- [00:37:53.841]can beet that satellite on there.
- [00:37:56.070]Next you need somebody that is placed in Australia.
- [00:38:00.573]Then our cloud begins to cover that.
- [00:38:09.310]I have a question about the automation
- [00:38:11.751]of the social networking people.
- [00:38:15.533]Have you heard that the base verification
- [00:38:17.811]of security still hasn't cleared?
- [00:38:20.194]Yeah, so I'm not sure that I did on that
- [00:38:22.952]particular project but there is another paper
- [00:38:26.359]that one of our techs just put out
- [00:38:28.532]what it did verify, I think they did,
- [00:38:30.789]yeah, I would verify as well.
- [00:38:34.655]I don't think well in that paper I don't think it's really,
- [00:38:37.177]but basically it's very good.
- [00:38:41.238]That's funny but there's a commercial product
- [00:38:43.850]shaped in Australia so you can sort of
- [00:38:46.930]do it on cats or cows relatively easily.
- [00:38:49.290]You could back and forth the odds.
- [00:38:52.043]It just takes a little work.
- [00:38:52.910]But with shaping lens you can see what it's for.
- [00:38:56.306]So there is a app for that out there and
- [00:38:58.584]it seems to be working okay.
- [00:39:01.468]It's just a little bit fussy.
- [00:39:08.722]Very cool applications for the technology.
- [00:39:12.001]One of the holy grails from the nutrition standpoint
- [00:39:15.140]is for GK.
- [00:39:16.810]Yes.
- [00:39:17.720]To experience that and the applications
- [00:39:21.110]is almost better to say for.
- [00:39:22.950]Yeah, so we've worked with the same equipment
- [00:39:29.576]in the technology industry it is relatively easy
- [00:39:31.959]to easily measure how much food is going down
- [00:39:34.132]and on the throat they can see how much weight gain
- [00:39:36.180]it puts on and make a version efficiency.
- [00:39:38.200]When it comes to pasture, it's really
- [00:39:41.250]quite technical to measure that.
- [00:39:43.641]It's a bit of an all day scenario.
- [00:39:45.438]Since our demo project for awhile
- [00:39:48.230]we're trying to do a sensor based approach
- [00:39:51.436]in detecting how much food is going down the gull.
- [00:39:54.362]You need to determine what is quite typical on the sensors
- [00:39:59.630]but how much is with what why some of my issue.
- [00:40:05.270]So some of the systems have called ink razor
- [00:40:08.280]which was sort of excavating or
- [00:40:12.063]it was getting a relative estimate of intake.
- [00:40:16.535]I won't fully admit it at the moment
- [00:40:19.649]but it is the holy grail.
- [00:40:22.032]Does it distinguish by group mating?
- [00:40:24.450]Or ingestion versus release?
- [00:40:27.319]Yes, yeah, I will say yes, yeah.
- [00:40:33.839]Other questions?
- [00:40:36.744]Haven't done any research on natural selection?
- [00:40:42.575]Come to actually synchronizing, trying to get MK on it.
- [00:40:50.240]Yeah, we have so in a couple of contexts.
- [00:40:53.730]So the boiling point to where the cows
- [00:40:57.643]walk across a platform and get weighed.
- [00:41:01.420]They also got a little bit of a waist tag
- [00:41:04.184]and a narrow id tag, so you can see them as they near you.
- [00:41:07.860]As they walk across the head, the training
- [00:41:10.453]would go have a drink and then go out.
- [00:41:14.230]What we found is you can actually watch
- [00:41:17.560]the wool falling behind that cow
- [00:41:20.667]and starting to peak up when she's excited.
- [00:41:24.960]So you get through that.
- [00:41:27.660]There's been a thing done with the accelerometer sensors
- [00:41:31.980]so both office fits in New Zealand
- [00:41:37.078]we are monitoring naturally with the
- [00:41:40.370]agent deputy with all of the evidence.
- [00:41:43.670]There is a bit of evidence there that works out quite well.
- [00:41:50.020]So my question is related to his question.
- [00:41:54.130]So I understand the use of this.
- [00:41:57.538]How is that being used for the ranchers
- [00:42:01.926]and that helping?
- [00:42:04.570]Yeah, sure so on one of that thinking
- [00:42:08.060]is in its infancy at the moment
- [00:42:10.683]but we just developed one that uses
- [00:42:12.527]in south Australia that tracks the
- [00:42:15.220]distribution of a shape over a grazing stage.
- [00:42:19.040]And what they do with that information
- [00:42:20.881]after they sat down and looked at it
- [00:42:22.574]and said, okay, I've got a feeling this is what's goin on.
- [00:42:25.370]It would be a lot like distribution.
- [00:42:27.590]But when he sat down with his objective data
- [00:42:30.181]and a map hard data, then he started
- [00:42:33.560]scrubbing around and moving in different areas
- [00:42:35.960]so they were utilizing generally.
- [00:42:39.800]I remember one particular situation
- [00:42:41.926]where you're driving in a very bare location
- [00:42:43.717]and look at it, very high standing polaris so
- [00:42:48.049]the sheep was basically just cut over here
- [00:42:53.399]and it had remained on it for a long time
- [00:42:56.179]and it went to another area
- [00:42:58.018]where it was quite heavily grazed
- [00:42:59.753]and it was relatively short and nutritious
- [00:43:01.810]so the sheep would be grazing there.
- [00:43:04.392]And then he went and called soil analysis and data
- [00:43:08.718]and so it went from happily grazing
- [00:43:11.560]they went up and built this monstrous thing
- [00:43:13.470]where it had been depleted.
- [00:43:16.388]So he's actually now implementing up there
- [00:43:18.352]with more fertilizer application approach based on the data.
- [00:43:25.228]Are you doing any work with drones?
- [00:43:27.443]A little.
- [00:43:30.536]My group tends to focus on the types of technology
- [00:43:34.480]that go onto the compartment of the drone itself.
- [00:43:37.960]So we've got producers out there with stray animals
- [00:43:41.424]with guns in Australia.
- [00:43:42.850]Which is quite easy application they made today.
- [00:43:46.590]Most of the work we've done was really quite,
- [00:43:48.650]we actually got something to measure
- [00:43:52.626]something that's of interest to the producer.
- [00:43:56.325]We also have some real regulation problems
- [00:43:58.747]that were in using drones in Australia.
- [00:44:01.810]So in our federal airspace authority
- [00:44:05.227]doesn't allow us to fly beyond the line of sight
- [00:44:09.344]and a few things like that which is what we really need.
- [00:44:17.670]So how far are we as producers from this technology?
- [00:44:21.988]How long to graduate our systems for it?
- [00:44:24.420]Yeah, so there's a few hurdles to get over first
- [00:44:27.920]and then the next couple, then the next couple.
- [00:44:31.690]But all the talk that there is,
- [00:44:34.780]say half the industry that the leading is
- [00:44:38.665]pushing really hard to try to overcome those.
- [00:44:43.576]But we have a really big task before us right now.
- [00:44:46.941]We have relatively lots of labor.
- [00:44:50.723]We don't cheat call, what we have.
- [00:44:52.760]We don't have much irrigation
- [00:44:55.739]and we don't have any sort of subsidies getting
- [00:44:59.290]so we're really driven by production efficiency.
- [00:45:02.340]So we got a set amount of money for each order.
- [00:45:05.180]As a bit of high price.
- [00:45:08.130]And so that sort of turn around in the industry
- [00:45:11.150]very cold that's on the map and what we always do.
- [00:45:16.000]The challenge in doing it is what these cost.
- [00:45:19.104]But it's coming together rapidly
- [00:45:21.988]and as that costs become relatively turns.
- [00:45:25.890]That's when this will really
- [00:45:28.905]be recognizable technology.
- [00:45:34.589]Excellent discussion.
- [00:45:36.345]We will try to leave here at about noon
- [00:45:39.981]or 1130 tomorrow.
- [00:45:42.020]If you would like to hear him again
- [00:45:43.820]just because you love his accent
- [00:45:45.610]or you love the information he is sharing or both,
- [00:45:48.820]he will be presenting to the graduate students
- [00:45:51.650]at three O'clock so you're welcome to join us.
- [00:45:54.109]Right down here, we got this class we are teaching
- [00:45:58.518]from the other day afterwards.
- [00:46:00.984]Say again.
- [00:46:03.158]128, okay, okay.
- [00:46:07.300]Alright, right over here.
- [00:46:09.120]At science room 128.
- [00:46:10.950]Tonight he's gonna be speaking at
- [00:46:13.800]block and bride at the grassland study students at seven.
- [00:46:19.438]So all of you are also invited back
- [00:46:21.140]to hear him then.
- [00:46:22.520]And after then there will be other opportunities
- [00:46:25.352]that can be made available.
- [00:46:27.212]So join me in thanking Dr.-
- [00:46:30.158](applauding)
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- Tags:
- UNL Department of Animal Science Seminars
- UNL Animal Science Department seminars
- australian grazing industries
- fenceless farms
- fitbits for sheep
- gps for cows
- laser beams in pastures
- mark trotter
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