Volume 11, Number 1
Radhouane Boughammoura, University of Monastir, Tunisia
The spread of COVID-19 virus (known as Corona) has an exponential growth all around the world. China, the epicenter of the epidemic, is the most infected country. Tell 07/04/2020, she count 81 740 infected, 3331 death and dramatic socio-economic consequences. At start we have believed that stay at home is possible solution, but next we have thought that this is not the right way as new mutated virus appears. So, as there are no medicines, the best solution is to coexist with the virus. Our approach is in this direction. Keep safe distance (1m or 3 feet) is the most relevant consign in order to surround the spread of the epidemic. Our approach is used to detect possible proximity of persons and to protect them in advance before contamination. We propose an algorithm, Barnes-Hut algorithm, based on Quad, a data structure which detects some proximity relative to persons and groups of persons. Alert is raised when the proximity between parsons is not respected. The algorithm can be used in decision making (e.g close frontiers). Experiments on real world dataset show the efficiency of the algorithm.
artificial intelligence, COVID-19 virus, person contamination, contamination detection, Quad, graphic design,