the defects of climate change. i mean, why are deforestation in the rain? forest continue, carbon dioxide emissions, and again, young people over the world are committed to climate protection. what impact will change doesn't happen on its own. the make up your own mind. a phone lines. the we have thing, extreme hate plus extreme rain these days. natural disasters like far as far as and funding of becoming increasingly common due to climate change. but how can the digital technology help us out? that's out topic today on ship the

whether it's mudslides in brazil of to heavy rain. destructive 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 here 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 inferno. before i thought as a using digital tech to track down and put out for us as early as possible. when a forest fire 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. i'm a licensed special like images and sensors on the ground, checking for smooth shifts and famel, infrared data that could indicate to fire. and this one is detected,

the 1st 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, simple imagery, whether it's a station or flame, 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. wild fires are hard to control. claims can change direction depending on the wind or they can spread at different speeds. by a map, predict california will suppress for the next hour. it's built on deep learning, instead of the web, the dryness of vegetation, historical fire premises and such a light blue ground sense of data. on this end, they have to move fast. any well equipped team needs the help of drones and extinguishing robots these days and the 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 comments 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, their 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 wild fires and real time. also, they can fly and smoky conditions or at night when it's dark and can carry water.

or they can be controlled with an app. the drones can be, can be easily effective. the smaller planes, especially because they can get quite close to the target without risking any lice . many fire fights this every die actually in point of why do you guys misses a so from that perspective, even if you've replaced life by like it's, it's a big advantage to technology not to expose you. most of those things just all i think the fine with that, but the best way to fight for as far as is to prevent them from breaking out in the 1st place. so once us 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 facing agency, works with computer modeling to create daily wildfire risk full costs. these full costs are usually based on geographic information systems o g i. yes. a computer system that analyzes geographically reference data, like maps,

street 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 the 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 droughts 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 have any user by next you finding a fire. so technology slowly, most useful in preventing 5 from happening, the 1st a cost, we can prevent every disaster because $1.00 thing is clear, extreme weather 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 hit 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 be calling really needed and they slowly, you know, percolating into into practice. one important task is combining the different types of data transmitted by satellites where people think of a satellite, even if they think about the colors. mostly because you know, we, we all use google not every day to, to buy their traits. 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 a 100 pets and this double machine learning specialist 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 and in each square, they simulate the physical process is key to forecasting with this way. 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 ride in one single rain storm in central europe. that the

spot, the fact that they would notified of the danger. however, countries like india, they've been struggling with the effects of climate change for decades. are well prepared for the 2013 sites and mainly mainland full in india. and although the 6th stream, the strong storm reached wind speeds of over 200 kilometers an hour and coast extensive, subbing just $22.00 people died. but a similar site close to 1999 killed 10000. so won't change the. the indian weather service now provides detailed holdings by text, message, email, phone, tv, radio, social, media, and other websites. the messages are 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, i'm 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 flux. we certainly shouldn't be seeing that number of depths from, from the kind of for the event. 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 meter in europe. we have very good at large investments in the science of climate change. and that gives us space, the big weather full cost models that can protect 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 local local communities. so there's still work to be done and what you are paying is could really learn a lot from all the countries. local emergency teams have to prepare as best they can for his offices. and so they need really good maps that are perfectly up to date. that's with humanitarian. open straighten up team comes in. the global n g o provides mapped off for disasters to achieve this employee open source programs and artificial intelligence. most of the times when it decides to happens where you would like to have the splendid stiffness, the permission to speak to you as possible to aid to be at this point. 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 upgrade and humble, you still making ups, but we use we didn't hot develop bi monthly or what to kim. and these,

we use them to speed up collection of real time points of interest. and we also have um, military, which we used to collect level imagery, did you have a real time to do what is happened? the map with a service helps users plus new data in open street map. the program uses machine learning to suggest the streets and pads the 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 areas where we will have deepening distress. we come my social media with some some sentiment that natalie just mentioned, learning technology to see if we can locate a better send drawings. we with the vision things, knowledge of the quote,

like highlights people on a roof or ask your gratian and this quote, for example, guides people on the ground that will then be able to save lives. even for me, it's an example of what for the assistant management 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, flies and droughts. 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 please. places in europe are smash the record. step into a little bit,

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70 years dw, the it is clear, the property is only for papers and that's for plastic. not that there's one for everything to address. so you have a priest from india in germany. you young? uh, yeah. you know, you just, uh dorothy is on, that's a german or a bit heart and low to be sense for you to enjoy tonight. and it's hard to many priests in germany, which is why i have come here to here, given the

frankfurt airport, the, the, to your diocese has sent a welcoming committee to meet their new creased father. she jo from tara lo south india, who becomes a census with common? yeah. a warm welcome to germany here. it's cold time. yes, i see the sun shining now, but this morning we had snow in the ground. each have a game. they don't have the jack is not even though they haven't been shopping yet because.