IOT Covid Bot

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dc.contributor.author Husnain Shafqat, 01-133182-035
dc.contributor.author Nabeel khan, 01-133182-071
dc.contributor.author Waqar Ahmad, 01-133182-131
dc.date.accessioned 2023-09-25T08:11:22Z
dc.date.available 2023-09-25T08:11:22Z
dc.date.issued 2019
dc.identifier.uri http://hdl.handle.net/123456789/16241
dc.description Supervised by Muhammad Yaseen en_US
dc.description.abstract By following to human social distance norms, transmission of COVID-19 may be avoided. It is possible to identify pairs of individuals who are not preserving a social distance limit of roughly six feet between them by using a revolutionary approach developed by us. No assumptions regarding crowd size or pedestrian routes are made in our system. An RGB-D camera and 2-D lidar are used to execute accident navigation in a population and calculate the distance between all recognized individuals in the camera's field of view. In order to determine whether someone has an excessively high temperature, security and medical staff employ a robot-mounted thermal imaging camera. An indoor CCTV camera system might help our mobile robot better identify social distance violations, correctly track people on the ground, and other such tasks. In a range of static and dynamic indoor environments, our technique's performance gains have been shown. en_US
dc.language.iso en en_US
dc.publisher Electrical Engineering, Bahria University Engineering School Islamabad en_US
dc.relation.ispartofseries BEE;P-2422
dc.subject Electrical Engineering en_US
dc.subject Robots in Covid 19 en_US
dc.subject Raspberry pi 3b en_US
dc.title IOT Covid Bot en_US
dc.type Project Reports en_US


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