i was lucky to have overcome this. as a reminder about top story, ukraine's precedence webmaster lansky has taken his leave from the g 7 summits in japan. so then he said he hopes the new piece plan, the code, and the war in ukraine and all conflicts around the world. that's all for now. i'll take magazine shift is next. don't forget our websites, dw dot com for the latest news. the knowledge since on we're on social media as well. i am eddie micah. julia, thanks for watching. staging from one use of the top of the the one of main kinds. oldest ambitions could be within reach.

what do you see? it really is possible to reverse the researchers and scientists all over the world for in a race against time. they are peers and arrival with one daring goals to help smart nature. the more likes watching it on youtube dw documentary, the we have thing xtreme hate plus extreme rain these days. natural disasters like far as far as and funding of becoming increasingly comment due to climate change. but how can the digital technology help us out? that's the topic today on ship the

weather. it's mudslides in brazil, off to heavy rain. destruct of tornadoes in the us or extreme heat waves in india, climate change impacts all of us fires are destroying many. hector has a forest both feet in berlin and across europe. never before has flat costs, so much damage here as in 2022 and people play an important role. well, it takes is picking one little cigarette but, and you might end up with a raging in front of the flood as a using digital tech to track down and put out for us as early as possible. when as far as via breaks out, there's no time to lose. but it might take residence hours or even days to report that special technology can help reduce that time to a few minutes. several companies work with also official intelligent software analyzes flashing light, images and sensors on the ground, checking for smooth shifts, and famel, infrared data that could indicate to fire. and this one is detected. first responders receive a notification. with machine learning,

we can actually teach the computers to identify on actual flame, or we can also teach that technology to determine if it's easy thermal imagery, whether it's a stationary lame, perhaps a power station compared to a moving plane for the last class. so in that sense of the terms of warranty or to make the detection is really important. wildfire is a hall to control. claims can change direction depending on the wind, or they can spread it different by a map, predict california will suppress. so the next hour. it's built on deep learning, instead is the web, the dryness of vegetation, historical fire perimeters, and such a light blue ground sense of data and this other software to simulate how wild fires will spread and health officials, direct firefighters and of actuation. once

all the data is available, it's time for the fly flight is to get to what to and they have to move fast. any well equipped team needs the help of drones and extinguishing robots these days. and there are even helmets that use old method reality to display useful information. let's take a look. innovative helmets also help firefighters on the ground. these helmets feature, augmented reality technology and thermal imaging, which enables firefighters to see through smoke and darkness. that way they can find and rescue people trapped by fires and bring them to safety more quickly. but things get really dangerous when firefighters end up trapped by fire. so that's where fire extinguishing robots coming. users can control them remotely from up to 200 meters away. and with a digital control station, the range can go all the way up to 2 and a half kilometers. users can guide the robot with it's built in cameras. drones can

provide additional safety. they are often used to transmit images and information on a wild fires and real time. also, they can fly and smoky conditions for at night when it's dark and can carry water. they can be controlled with an app. jones can be, can be easily effective. the smallest lanes, especially because they can get quite close to the targets without risking any lice . many fire fights this every die actually in point of what you guys missed was a so from that perspective, even if you replace life by like it's, it's a big advantage. the technology not to expose you. most of those things just all i think the fine with that. but the best way to fight for us was, is to prevent them from breaking out in the 1st place. so it says over the world of working on systems to predict where and why something might catch a lot. and in california they've come a long way in finding answers to those questions. california is via slicing agency works with computer modeling to create daily wildfire risk phone call. these full

costs are usually based on geographic information systems or g i. yes. a computer system that analyzes geographically reference data, like much, st buildings and vegetation. the simulations can help identify risk areas because they are densely populated. to have a lot of dr. agitation. the authorities come then sign accordingly. for example, removing the dead trees that could become fuel. so while the effects of the climate crisis, such a severe sheets and drought of fueling wild fires, today's technology is improving the precision of early warning systems. it's much better to identify the risk for fire and also having to use my nephew finding a fire. so technology slowly, most useful in preventing files from happening in the festivals. of course, we can't prevent every disaster because one thing is clear, extreme went on, isn't going to go anywhere. and i'm not just talking about extreme hates causing

drops and fires. heavy rain will lead to flooding as well. so that's why it's important to be well prepared with precise where the full costs satellites regularly transmit the latest data. and that data needs to be analyzed and assessed quickly. but that's almost impossible without artificial intelligence. meteorologist to rely on local observations and also assess data transmitted from over $800.00 weather satellites. the key to analyzing this data as quickly as possible often involves machine learning. we have so many satellites up in the air now. and so they give us the time data and it's, it's like a mountain of data. so if we have heat the points where it's just not possible to do it by hand anymore, it's just not possible to do anything a time. that is the time that we need for intervention. so i think that these technologies always becoming really needed and they slowly, you know, percolating into into practice. one important task is combining the different types of data transmitted by satellite where people think of the human to think about the

colors. let's see. because, you know, we, we all use google not every day to, to buy their trades, but it's not pleasant, but much different types of data. you know, when there is a storm, it's very cloudy and traditional stuff that i do not see anything, for example. so people tend to use radar data for that. there was a lot of these different satellites, or between about 4 pets and this the double machine learning, especially like nice try to make sense of all of them together because everyone completes the weakness of the other. the cleaned up data can then be entered into computer models to simulate the physics of the atmosphere and oceans. these models divide up the world into a grid at an inch square. they simulate the physical process is key to forecasting with. this with the models can estimate what the weather will be like in the coming days with a high degree of precision. but what good are

the best calculations if residents not notified? or if i don't take the warning seriously, in 2021 over 220 people died in one single rain storm in central europe. that the spot the fact that they would notified of the danger. however, countries like india that have been struggling with the effects of climate change for decades are well prepared for the 2013 sites, the mainland mainland full in india. and although the 6th stream least strong store reached wind speeds of over 200 kilometers an hour and coast extensive studying. just 22 people died. but a similar psych loan in 1999 till 10000. so won't change the. the indian weather service now provides detailed warnings by text, message, email, phone, tv, radio,

social media and other websites. message is spread locally to the people follow their instructions. but the situation in europe is completely different and people are not yet taking the effects of climate change. serious in 2021. the storm in germany, belgium and the netherlands killed more than 220 people as scientists, we were, we were really shocked by, by the, the scale of the impact of the floods. we certainly shouldn't be seeing that number of depths from, from the kind of further then the flooding was devastating. even just spice extensive research on early warning system. now though, in the city of austin and western germany, a risk based rain warning system which is under development is meant to predict precipitation amounts down to the square meters in europe. we're very good at large investments in the science of climate change. stock gives us those,

the big weather full cost models that can predict things, but the further ahead of an event. but what we really need to do is understand the decisions that are being made in those live local communities. so that still work to be done. and what your opinions could really learn a lot from all the countries local emergency teams have to prepare as best they can forward as offices. and so they need really good maps that are perfectly up to date . that's with humanitarian open, straight map team comes in. the global n g o provides mapped off for disasters to achieve this state employee open source programs and artificial intelligence. most of the times when it developed a happens where you would like to have sister spun does, do you see permission to speak to as possible to 8 to the response so, but to be safe people's lives. online volunteers from across the globe can help

provide data for regions that are unmapped or have errors or they can update them after natural disasters. and the digital technology really helps. we have quite a number. you still maybe ups, but we use within hot develop but mostly of what to kim and this we use them to speed up collection of real time points of interest. and we also have um, my buddy, which we used to collect level imagery. did you have a real time to do what is happened? the map with a ice surface helps users plot new data in open street map. the program uses machine learning to suggest the streets and pads that humans later have to verify and maybe add missing details to the combination of human and artificial intelligence is meant to help with responding to natural disasters quickly and adequately. we will have a system where a satellite imagery looks at the place that they've been as being flooded. for

example, the identified gary as we will have deepening distress within my social media with some some sentiment that knowledge is machine learning technology to see if we can locate a better sam drawings. we wouldn't be just acknowledging that was like highlight people on a roof for rescue a ration. and this quote, for example, guided people on the ground that will then be able to save lives. if it's for me, it's an example of what for the assistant intelligence system that will be very useful satellite pictures, drones and image recognition software based technologies can save lives during natural disasters. all right, and it's good. the things designs us, we can react better to storms, flyers and drafts. now, do you receive digital warnings before natural disasters struck in your country? let us know and write to us on youtube and the w dot com. thanks for watching and see you next on the

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