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This paper describes a configuration of drone swarms that can be used to limit the virus spread during a pandemic period, such as the COVID-19 emergency. The proposed study analyzes a system architecture to support the identification of targets affected by the virus, estimating the biomedical parameters. The presented method exploits different techniques, such as stereoscopy vision, thermal measures and remote photoplethysmography to acquire standalone data that can be compared to evaluate the target risk. The tested solutions are proposed to measure the social distancing among more targets, the skin surface temperature of a target person, and the image photoplethysmography signal, that are critical parameters to detect a target disease during the COVID-19 pandemic. Different test strategies were adopted to achieve the mentioned tasks. To measure the skin surface temperature of a target, a drone equipped with a thermal camera was adopted, performing measures at different distances and heights. To measure the distance between two fixed targets, two drones equipped with visible band cameras were employed. To obtain the image photoplethysmography signal, a video file from drone camera is processed. Image processing techniques are required to elaborate the data coming from several images and videos acquired by drones. Comparing the estimated results, altered biomedical parameters of several targets can be detected and later tested with medical equipment.
University of Naples Federico II / University of Bergamo, Italy
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Download from Proceedings of IEEE 2021 International Workshop on Metrology for AeroSpace