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Smart city article details
| Title | Video-Based Social Distancing: Evaluation In The Cosmos Testbed |
|---|---|
| ID_Doc | 61117 |
| Authors | Ghasemi M.; Yang Z.; Sun M.; Ye H.; Xiong Z.; Ghaderi J.; Kostic Z.; Zussman G. |
| Year | 2024 |
| Published | IEEE Internet of Things Journal, 11, 3 |
| DOI | http://dx.doi.org/10.1109/JIOT.2023.3305587 |
| Abstract | Social distancing is an effective public health tool to reduce the spread of respiratory pandemics such as COVID-19. To analyze compliance with social distancing policies, we design two video-based pipelines for social distancing analysis, namely, automated video-based social distancing analyzer (Auto-SDA) and bird's eye view social distancing analyzer (B-SDA). Auto-SDA is designed to measure social distancing using street-level cameras. To avoid privacy concerns of using street-level cameras, we further develop B-SDA, which uses bird's eye view cameras, thereby preserving pedestrian's privacy. We used the COSMOS testbed deployed in West Harlem, New York City (NYC), to evaluate both pipelines. In particular, Auto-SDA and B-SDA are applied on videos recorded by two of COSMOS cameras deployed on the 2nd floor (street-level) and 12th floor (bird's eye view) of Columbia University's Mudd building, looking at 120th St. and Amsterdam Ave. intersection, NYC. Videos are recorded before and during the peak of the pandemic, as well as after the vaccines became broadly available. The results represent the impact of social distancing policies on pedestrians' social behavior. For example, the analysis shows that after the lockdown, less than 55% of the pedestrians failed to adhere to the social distancing policies, whereas this percentage increased to 65% after the vaccines' availability. Moreover, after the lockdown, 0%-20% of the pedestrians were affiliated with a social group, compared to 10%-45% once the vaccines became available. The results also show that the percentage of face-to-face failures has decreased from 42.3% (prepandemic) to 20.7% (after the lockdown). © 2014 IEEE. |
| Author Keywords | COVID-19; object detection; smart city; social distancing; testbeds; tracking |
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