ENHANCING PASSENGER HEALTH PROTECTION USING SOCIAL DISTANCING MONITORING SYSTEM AT AIRPORT TERMINAL

• Main Author: Iman Putra, Rizaldy
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/77798
• Institution: Institut Teknologi Bandung

With the growth of air transportation passengers increasing every year, passenger health protection is an aspect that must be monitored by the airport. This aspect must be increasingly emphasized because in 2020, the COVID-19 outbreak hit the whole world and affected airport operations. The airport has made efforts to minimize the spread of COVID-19, such as implementing social distancing. With the help of artificial intelligence (AI), the airport can monitor the safe distance between passengers using terminal area surveillance cameras. This undergraduate thesis presents the development of a tool or dashboard to monitor safe distances between passengers at airport terminals using video data. This video data is then analyzed using the YOLOv4 object detection model which is trained to detect humans. A total of 300 data were used to create an artificial intelligence model in this research. Then this model is used on the dashboard to detect the safe distance between detected passengers. The dashboard successfully detects the number of passengers violating social-distancing and crowd density, also displays the results in the dashboard in the form of detection result images, passenger density metrics, percentage of passengers detected violating social distancing, and historical graphs of the number of passengers detected violating social distancing and passengersdetected not violating social distancing. The developed tool or dashboard can be used by the airport or airport service providers to monitor the safe distance between passengers at the airport terminal to protect the health of passengers and by service users to get the best service from the airport.