Use of Barnes-Hut Algorithm to Attack COVID-19 Virus


Radhouane Boughammoura, University of Monastir, Tunisia


The epidemy COVID-19 (khnown as Corona) is very dangerous. China, the epicenter of the epidemy, is the most infected country tell 07/04/2020 with 81 740 infected, and 3 331 death. To limit the exponential propagation of the virus we have to respect some consigns. Keep safe distance (1m or 3feet) is the most relevant consign in order to surround the spread of the epidemy. Our approach is used to detect possible contamination of persons. Barnes-Hut algorithm is based on quad, a data structure which detects certain 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 shows the efficiency of the algorithm.


COVID-19, person contamination detection, quad, query search, graphic design, artificial intelligence