In some countries, including the US, we have already seen using drones to assess the likelihood that they will be used to track whether social distancing protocols are being implemented. More sophisticated applications are on the horizon, such as drones with the potential to recognize signs of COVID in people inside a crowd, such as elevated temperatures. To analyze data collected by drone cameras, these programs use machine vision technologies to notify officials or municipal administrators of statistics and risks about transmitting the virus.
The use of facial recognition technologies, also driven by computer vision algorithms, will be another related growth field. The police have used facial recognition to identify lockout and quarantine avoiders and trace persons’ movements showing symptoms within a crowd. It focuses on the identity of individuals rather than patterns between groups of individuals.
The research appears to indicate that, owing to the health threats posed by the outbreak, the population has been more accepting of monitoring techniques that may traditionally have been considered excessively stringent. As technologists grow more adept at AI-driven monitoring and even compliance, this tolerance is likely to be more checked over the coming 18 months. As technologists grow more adept at AI-driven monitoring and even compliance, this tolerance is likely to be more checked over the coming 18 months.