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Intel uses AI and satellite pictures to assist the Red Cross map defenseless locations

In the last five years, the United States of America Red Cross, the British Red Cross, the Doctors without Borders and the Humanitarian Open Street Map Team started the Missing Maps Project, a humanitarian attempt aiming to map portions of the planet vulnerable to wars, disease epidemics and natural calamities preemptively. Thus far, its mapmakers have contributed statistics on cities and towns in nations such as South Sudan, the Central African Republic and the Democratic Republic of Congo, which organizations have made use in a bid to pursue the displaced populations’ movement and to recognize the sources of the outbreak of diseases. 

Archaeologically, the majority of the mapping procedure has been undertaken manually. The humanitarian organizations identify vulnerable locations and design preliminary maps, after which the field members labor with local civilians to travel to the places on the map and input the names of the critical areas while looking for errors. The volunteers are responsible for locating swamps, rivers, and other ordinary landmarks on to the imagery of the satellite, and handing over the gathered information to an online portal to be widely distributed. 

In the look of a fresh approach that may assist, expedite the procedure, Intel in early 2019 united with the Red Cross to give technology, which identifies formerly unmapped roads and bridges on satellite pictures. The organization states that the AI model “significantly” supplements volunteer mappers’ capabilities to cover further ground to catch things impossible for the naked human eye to observe. 

Dale Kunce, who is the co-founder of Missing Maps and the Chief Executive Officer of the American Red Cross Cascades Region, stated that there are whole parts of the planet that are unmapped. This makes responding and planning to calamities much more problematic. He added that this is the reason why they are cooperating with Intel to use AI in mapping vulnerable locations and identifying bridges, roads, buildings, and cities. 

While plotting Uganda, for example, Intel’s computer vision model that operates on second-generation Intel Xeon Scalable processors with DL boost and graph discovered 70 bridges on the southern side of the nation missed by either OpenStreetMap or the Bureau of statistics map of Uganda.  Kunce added that like someone always on the ground with the Red Cross, having admission to precise maps is exceptionally crucial in calamity planning and response to the emergency. 

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