Muhammet Fatih AslanKhairunnisa HasikinAbdullah YusefiAkif DurduKadir SabanciMuhammad Mokhzaini Azizan2024-05-282024-05-2820222022-11-11Aslan MF, Hasikin K, Yusefi A, Durdu A, Sabanci K and Azizan MM (2022) COVID-19 Isolation Control Proposal via UAV and UGV for Crowded Indoor Environments: Assistive Robots in the Shopping Malls. Front. Public Health 10:855994. doi: 10.3389/fpubh.2022.8559942296-25652494-2210.3389/fpubh.2022.855994https://www.frontiersin.org/articles/10.3389/fpubh.2022.855994/fullhttps://oarep.usim.edu.my/handle/123456789/6592Front. Public Health, 31 May 2022 Sec. Digital Public HealthArtificial intelligence researchers conducted different studies to reduce the spread of COVID-19. Unlike other studies, this paper isn't for early infection diagnosis, but for preventing the transmission of COVID-19 in social environments. Among the studies on this is regarding social distancing, as this method is proven to prevent COVID-19 to be transmitted from one to another. In the study, Robot Operating System (ROS) simulates a shopping mall using Gazebo, and customers are monitored by Turtlebot and Unmanned Aerial Vehicle (UAV, DJI Tello). Through frames analysis captured by Turtlebot, a particular person is identified and followed at the shopping mall. Turtlebot is a wheeled robot that follows people without contact and is used as a shopping cart. Therefore, a customer doesn't touch the shopping cart that someone else comes into contact with, and also makes his/her shopping easier. The UAV detects people from above and determines the distance between people. In this way, a warning system can be created by detecting places where social distance is neglected. Histogram of Oriented-Gradients (HOG)-Support Vector Machine (SVM) is applied by Turtlebot to detect humans, and Kalman-Filter is used for human tracking. SegNet is performed for semantically detecting people and measuring distance via UAV. This paper proposes a new robotic study to prevent the infection and proved that this system is feasible.enCOVID-19, HOG, SegNet, semantic segmentation, Support Vector Machine, UAVArticle113102022