Managing the interaction of persons and the formation of crowds has become a key priority in our efforts to flatten the COVID-19 curve. Deploying enforcement personnel to manually monitor social interactions and social distancing is a tedious task and prone to errors.
NTU’s Rapid-Rich Object Search (ROSE) lab collaborated with the Defence Science & Technology Agency (DSTA) to deploy a full scale visual analytics solution at selected large scale COVID-19 recovery facilities, endowing the facilities with enhanced capabilities that better encourage socially responsible interactions among the thousands of tenants. This deployment was based on the interim deliverables of a research project funded by DSTA and AI Singapore, with Prof Alex Kot, Director of the ROSE Lab, as the principal investigator.
The suite of visual analytics software processes real time surveillance camera footage, detecting, tracking and associating people observed in different views of the camera network. It enhances awareness of personnel movements within the compound and empowers our social distancing ambassadors to step up the fight against the spread of the deadly virus. The benefit is more productive and effective use of onsite personnel for managing the tenants and contractors at these recovery facilities.