A computer vision-based object detection and counting for COVID-19 protocol compliance: a case study of Jakarta

The chaotic world situation caused by the SARS-CoV- 2 virus (COVID-19 pandemic) has hampered many sectors of human activity, especially in activities that require physical interactions. Thus, requiring social restrictions for those sectors that are affected. This paper reports the analysis of the proposed system for monitoring and supporting public activities in order to carry out social restrictions, specifically in the DKI Jakarta province. The proposed systems are YOLO and MobileNet SSD as its main weight to help this detection system with 30% and 40% confidence, respectively. The results of object counting and physical distancing are expected to be a guideline for public complaints in the future by using several CCTV locations points with better image quality and better angles.