the shuttle the currently move people the on the world wide in such a hassle it as a committed god the castle. josh. find out about robina story info. my grands we're living in an area of mass extinction. one unmatched. and the last 6 to 6000000 years since the dinosaurs were wiped out over a quarter of old mammal species. and one in a species are on the brink. but kennedy, i help save them today on shift and it is not only natural, these offices and climate change that threatened wildlife po chose, for example, can over $20000.00 african allison's every year ranges and national parks have been struggling to prevent the practice. but that's non profit organizations. heck the

planet has developed in a i camera system to detect poachers and sound the alarm in real time. and a trigger wanting us might find some of the following imagery distressing. african ellison populations have fallen drastically in the last century. one major cause poachers, they want their ivory to stuff them the non profit organization. heck the planet has found a way to modify the existing camera trips these uh, these cameras, we call them the dump cameras. we. we make them smarter, so we modified, i'm a little so um, so that they're unable to communicate with a box that we created. we manufacture these and make them able to communicate and send the photos wirelessly. and we analyze these photos using ai. so we have a machine learning algorithm on there and analyzes the photo, and then we immediately know what's on the photo if it's a human origin. alison,

if a person is detected and alert, isn't arrangers immediately. this way they can react quickly to potential poachers, which wasn't possible before these range are units. oftentimes they just find an edison's carcass. uh and, you know, then then the poachers are already gone like maybe one week or 2 weeks ago. and they don't have any information to go from because it, you know, they don't know where they came in or where they went out. because it's such a huge area, the, the smart devices make is much more likely to catch intruders in real time. they work via satellite and don't need why fi? the countries like come on sandia and some bob way have already implemented the smart camera trends. for the endangered african elephants and those who protect them. the technology could mean the difference between life and death.

in india, amazons, and killed a different dangers to around 20 of them. i ship and killed by trains every year. that's why in a i warning system is being installed a long railroad tracks sense those identified vibrations on the ground caused by elephants and sent a warning signals to prevent collisions. it's undoubtedly an issue, but one was by the threat of global warming. 2023 was characterized by devastating fires around the world. greece, spain, hawaii, canada. in australia i, technology is now being used to help protect animals like the kangaroo and the koala. from the effects of bush fires, a koala is on the move under the cover of night. just like these qualities, the kangaroos, smaller cousins for australian wildlife conservation of these images are a small victory. using camera traps,

they are trying to find out how well different animal species are recovering from bush fires. so the camera takes the animals by a combination of movement and hate from the animals. so as the animal looks past the camera, usually a man with a bite station is if it gets triggered and takes 5 quick photos of the animal as it comes past guess on the teen. aaron greenville researches in the iconic blue mountains west of sydney. the area is a tourist draw, but is also prone to bush fires. that's why it was included in w w. f. us really is large scale camera sensor project i, as on recovery of about 1100 camera traps were installed all over the country, especially in areas damaged by the bush fires of 20192020. the cameras generate millions of photos helps researchers analyze the data. ready

the artificial intelligence is actually enabling them to sort through these images much more, much more rapidly. so it's basically improving their efficiency so they can go out and do you know the work of the work that they need to do to manage that have spaces recovery, for instance, after collecting the photos from the cameras, researches upload them to an, a model called wildlife insights the google powered platform has a database of over 35000000 images and is being used by wildlife organizations all over the world. detects what kind of animal is seen within an image and labels that accordingly helping research move along more quickly. ready that we find ourselves in this point in time where climate change is is meaning we're having more frequent fires, not just in australia, but across the entirety of the world. so projects like eyes on the cover that

developed technology that can help us to assess impacts more rapidly just absolutely crucial for understanding future fire events in australia and across the world. well, the blue mountains look lushin green. now, it is just a matter of time before the bush fires return and the animals suffer. the system won't save the animals in the event of this aspect, but knowing where they live and how many they are is extremely important for conservation. but how do the databases work? we asked them to explain it for us. it's as easy as drag and drop. researchers upload photos to one's life insights within seconds, image recognition, i identify as the animal. so when a research or a biologist uploads their camera trap data to the wildlife insights platform in our

artificial intelligence model, most of the images and based upon what we, what we shown it before, it makes the predicts on what it thinks it sees inside the image. the i matches the photos to animals that has been trying to recognize the database contains entries for over 3000 animal species. a value of one means absolute certainty. so 0.99, just from this image of an elephant, the trunk is very close. indeed. va isn't always that confident. for example, when distinguishing a leopard from a judge, you are on some platforms d, i can even recognize individual anonymous. sharks, for example, have unique patterns on their skin. would you like caused them to be identified? the algorithms den much the patterns like facial recognition software. ready

wireless can be clearly distinguished by their tail fins, allowing researchers to learn more about their movements box and turn can lead to better conservation for the marine jones. but sometimes pictures alone, the enough waves, for example, rarely come to the surface. that's why scientists also use towns to find out more about them. sounds like this. what do you hear a because of the barriers weight of specie is recorded in alaska? sound samples like these are collected worldwide. the problem, microphones, folding victim to interference, but with the use of a i, we so it says that able to feel that the interference out and here they called and our feeling is mostly an efficiency thing. if you apply a i, it kind of figures out the easy decisions for you, and then it lets your expert look at the areas where they,

i'm so sure. and it allows the experts do with the past to validate. and the a, i really takes a lot of them like brute force out of that. so we've estimated that it saves as much as like 96 percent of our time. the sounds can even be assigned to individual way of specie is sped. why is this important? well, some specie is like this right away, and here, critically and agent, we found a call like just kind of a cryptic call. we didn't know who it belonged to, but we thought it might be a essentially right, we'll call. we're able to search our entire lives. we would never been able to do that without a i, and for a population of 30, you know, every data point counts because they're super rare, you really don't expect to find them. so having, having tools that allow you to call these huge datasets, leave no stone on terms a, this is essential for populations like that. but it's not just the ocean designs that are threatened with extinction. insights in particular addressed european populations are declining sharply, but a i can help you too,

by showing us what these really need to try to design their own garden. it would look like this. at least according to alexandra daisy ginsburg, the garden in front of berlin's natural history museum as her art project. as an algorithm, as chosen which plants arctic ro here. every time we run the algorithm to create a new prompting scheme, the algorithm is optimizing the tom thing choices and arrangements to have the most diverse group one and 18 species possible. so these were most and many more following the algorithm, specifications, ginsburg entertain, planted 7000 plants, here in the heart of berlin. the project is called pollinate, or pass maker to develop the algorithm, ginsburg and her team researched the exact needs of local pollinators. the

algorithm then generated a planting schematic with $150.00 plants. species even calculates how the garden will change throughout the year. the, the algorithm chooses plots that are appropriate for each location for the soil conditions, sunshine, so on. and then it arranges, it takes a subset to create unique schemes every time. i'm then arranging them in ways that see different charging style up to my business as a whole. different insect pollinators locate their food in different ways. some insects, such as bees memorize the locations of flowers and develop efficient flight routes to visit thousands a day. or the i will look most on tcp of the algorithm anticipates the pollinators flight path. so we'll see, that's what the planting pattern is based on the data for the men,

special olga when the voice. oh, it's a, it's of a, it looks unusual to the human eye, but it's designed around the weight and sex. moved around the garden in the garden, just i don't answer. then. you can use the algorithm yourself to calculate a plan for an insect friendly garden, free of charge. the web based tool is optimized for your opinion, wildlife, but models for other regions could soon follow hey, i can go through a huge amounts of data very quickly helping us understand lots of greenery and even large and complex eco systems. this new technology has become an integral part of conservation. that's all from me. take care to him next time by the

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