{"id":245086,"date":"2021-05-07T15:54:51","date_gmt":"2021-05-07T12:54:51","guid":{"rendered":"https:\/\/en.buradabiliyorum.com\/3d-detectors-measure-social-distancing-to-help-fight-covid-19\/"},"modified":"2021-05-07T15:54:51","modified_gmt":"2021-05-07T12:54:51","slug":"3d-detectors-measure-social-distancing-to-help-fight-covid-19","status":"publish","type":"post","link":"https:\/\/buradabiliyorum.com\/en\/3d-detectors-measure-social-distancing-to-help-fight-covid-19\/","title":{"rendered":"#3D detectors measure social distancing to help fight COVID-19"},"content":{"rendered":"

“#3D detectors measure social<\/a> distancing to help fight COVID-19<\/strong>”<\/p>\n

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\n Alexandre Alahi (left) and Lorenzo Bertoni (right) in the Visual Intelligence for Transportation Laboratory at EPFL. Credit: Alain Herzog \/ 2021 EPFL
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A team of EPFL researchers has repurposed an algorithm they initially developed for self-driving cars to help people comply with social distancing requirements. Their program, which works with a camera, can detect whether individuals are maintaining the right distance to prevent infection\u2014without collecting any personal data. It could be useful for public transport systems, in shops and restaurants, and even in factories.<\/p>\n

“When Switzerland went into lockdown last year, we were working on an algorithm for self-driving cars,” says Lorenzo Bertoni, a Ph.D. student at EPFL’s Visual Intelligence for Transportation (VITA) Laboratory. “But we quickly saw that by adding just a few features, we could make our program a useful tool for managing the pandemic.” The VITA lab is headed by tenure-track assistant professor Alexandre Alahi.<\/p>\n

After spending several weeks reading up on how the COVID-19 virus is spread, Bertoni and his team began to realize\u2014along with the rest of the scientific community\u2014that microdroplets play a key role in spreading the virus and that it’s essential for people to maintain a distance of at least 1.5 meters if they’re not wearing a face mask. The researchers therefore began tweaking their algorithm, which was initially designed to detect the presence of another car or a pedestrian on the road and instruct the self-driving car to slow down, stop, change direction or accelerate. The researchers just published their work in IEEE Transactions on Intelligent Transportation Systems<\/i> and will present it at the International Conference on Robotics and Automation (ICRA) on 2 June 2021. <\/p>\n


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