Facing the criticality of the COVID 19 pandemic, we propose an artificial intelligence system with a modern approach detecting people and their social distancing in crowded places using thermal images obtained from the DJI Mavic 2 Enterprise Dual drone. We implement an algorithm that analyzes two types of images: color and thermal, to measure the distance between people. We used the Fast R-CNN neural network; the images with videos were extracted from the DJI Pilot application. The objective is to identify the distance between people. The results obtained show that the proposed algorithm is suitable for monitoring the city.

This work focuses on studying the relationship that existed between the use of the learning management system (LMS) and the academic performance of the students of the Jorge Basadre Grohmann National University of Tacna-Perú. For this, we use the data provided by the LMS (access virtual classroom) and the university's academic management system (grades). For that, we perform various classification machine learning algorithms to predict academic performance with two classes SATISFACTORY or POOR where Gradient Boosted Trees algorithm had the best accuracy 91.79%. However, with three classes, SATISFACTORY, REGULAR AND POOR, Random Forest algorithm had the best accuracy of 89.26%.