Location Proximity of Covid-19 Suspect Using Mobile Data History

Dealing with the startling challenges caused by the pandemic has taken a notable toll on the lives of the people all across the world. The novel coronavirus (SARS-CoV-2) causes a respiratory illness called COVID-19 which is contagious and currently a potential threat to mankind. The virus can have effects ranging from mild to severe with the risk of deaths. The rise in the number of cases is generally because of the unknown travel history of the person during the pandemic. The government has taken a multi-pronged strategy like lockdown, self-isolation, etc. to lessen the spread. This paper proposes a more efficient way which will help to reduce the spread of the virus with the help of a data analysis technique using the MATLAB programming environment. Data analysis will help in analyzing and visualizing the travel histories of the person which will be useful for the detection of location proximity because of which the risk of spreading COVID-19 is high. Along with the location, the date, time, latitude, longitude and distance can also be known. For this analysis, Google timeline history is used which is more effective in terms of accuracy, activity tracing and data storage than the traditional technology of tracking cell phones by towers or by manually questioning the person about the places he/she visited.