CoVANET: A VANET application for detecting and tracking COVID-19 cases in real-time

By the time of writing this paper, countries around the world are in a race against time to reduce or stop the spread of SARS-CoV2 (COVID-19) virus. Relying on typical measures such as social distancing to partial and full lockdowns seems to be insufficient. However, involving modern technologies should be sought after in order to support the efforts by governments’ measures to decrease the spread of virus. Vehicular Ad-Hoc Networks (VANET), among many other technologies, can fit into the current scene. Through their Onboard Units (OBU), and by leveraging modern communication technologies, vehicles can play a vital role in reducing the spread of COVID-19 and minimize the effects of the pandemic. In this paper, a VANET application layer model for monitoring and detecting COVID-19 symptomatic cases is proposed. In the proposed model, a vehicle's OBU senses the vehicle's driver and passengers’ temperature for any abnormalities, warn surrounding vehicles as well as any Roadside Units (RSU) within the transmission range with warning messages containing the detected case's temperature, and the vehicle's coordinates and identification. The information disseminated from the vehicles to the RSU is used to track the vehicles and take actions accordingly. The proposed model presents and expansion to the current VANET safety and healthcare applications by utilizing the available distant thermometers and current wireless communication. A proof of concept model that can monitor, detect, and warn in the case of the existence of vehicles with fever symptomatic cases of COVID-19 in.real-time was developed and verified using simulation.