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A Queue Management Approach for Social Distancing and Contact Tracing

Social distancing is necessary to prevent the rapid spread of a highly contagious disease, such as COVID-19, at least until a vaccine is found and mass-produced. By reducing the probability of an uninfected person coming close or in physical contact with an infected one, the disease transmission in the community can be suppressed. Although social distancing is simple to comprehend, it is not always easy to implement, mainly because not all public spaces are designed with this requirement in mind. In this paper, we present a queue management tool that can be used to allow people that wait for a service practice social distancing. In our approach, people are asked to join a virtual queue, in order to avoid crowds in physical waiting rooms or long waiting queues. Machine learning is used to predict the estimated waiting time of queuers, so they are called just in time to get served. We use past data and machine learning to predict how busy a location will be so that customers can pick the best time to visit the service. Finally, we present the method we use to monitor people taking a service at any time and implement contact tracing in a privacy-preserving manner.