A Fog Computing Simulation Approach Adopting the Implementation Science and IoT Wearable Devices to Support Predictions in Healthcare Environments

The world is facing a grand challenge with the unexpected pandemic caused by the Sars-CoV-2 virus. Several researches are underway to understand more about the virus, its way of spreading in environments and prevention methods. Even in a short period, it was possible to obtain recommendations to assist in the control of contamination, and some parameters of those are the use of masks and social distancing. In this study, we considered the implementation science concept in a simulation effort based on changes in habits and behaviors related based on prevention methods. In addition, in our work we also considered the utilization of wearable IoT devices for monitoring people who live in environments where social isolation is complex. We conceived four scenarios with different prevention approaches and isolation, where the health data of the simulated agents were collected for monitoring and providing predictions. The implementation science approach, together with wearable IoT devices, provided a differentiated view from all environments. Agents that have more preventive habits got contamination rates of 12.11% against the worst scenario, with 77.00%.