Around the reality , metropolis arechokingonsmog . But a new AI scheme plans to analyze just how bad the situation is by aggregate data from smartphone pictures get far and wide across cities .
The project , called AirTick , has been developed by investigator from Nanyang Technological University in Singapore , account New Scientist . The logical thinking is pretty simple : deploy air detector is n’t cheap and takes a long metre , so why not make use of the sensors that everyone has in their pocket ?
The event is an app which allow hoi polloi to account smog levels by uploading an image trail with time and location . Then , a machine learning algorithm masticate through the data and compares it against official air - quality measurements where it can . Over clock time , the squad hopes the software will slowly be capable to predict aura timbre from smartphone images alone .
There ’s room for error , of course : misfortunate images or strange exposure could confuse it . But results taken in total should permit the organisation to head off fault due to such causes . The idea , after all , is n’t to cover smogginess levels from a single photo , just to provide insight into contamination stratum more topically than can be achieved right now .
The results could be used to warn people when smog levels are too high-pitched for , say , asthmatic children to venture to the ballpark , or to allow citizenry to schedule their physical exercise so they ’re not running during peak smog . The project will be lay out at the AAAI Conference on Artificial Intelligence in Phoenix , Arizona , later this month .
[ New Scientist ]
picture by AP
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