George-Alexandru NEAGU, Stefan-Alexandru MITACHE and Mihai REBENCIUC
Center for Research and Training in Innovative Techniques of Applied Mathematics in Engineering, University Politehnica of Bucharest, Bucharest, Romania
Volume 2020 (7),
Article ID 36106420,
AI, Data Mining and Data-Driven Solutions in Different Fields: 36AI 2020
Abstract
Since the 2020 Covid19 Pandemic people have tried to find various ways to prevent humanity from catching this virus and one of the best examples is China’s Corona-Virus application. In this regard, we are creating Covid19 Sentinels which are robots with thermal vision that will especially be placed in areas with a high infection rate and have the role to detect if pedestrians have the Corona-Virus temperature which was agreed through convention that is roughly 37.3 degrees Celsius. Let’s say there is a Covid19 static Sentinel in a shop and 4 men enter the shop. The robot will analyze each individual then it will decide if any of them is infected and if one of the individuals is infected then the alarm will trigger. The robot gather some important data from each pedestrian and the most important ones are distance and the temperature as the robot needs to be at a certain range to be very precise so there are not any false alarms; the machine has a set of rules according to Grammatical Evolution based on context free grammar. An future improvement for Covid19 Sentinels are a laser that can pinpoint the infected individual.