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It describes the progress that has been made in the "Smart Campus" project, which is being carried out at the Instituto Tecnológico de León. The objective of this project is to improve the stay of the people who walk through the institution on a daily basis, using intelligent agents, artificial intelligence, the internet of things, software, databases, hardware and platforms that the University already has, using the traditional architecture to its advantage and adding certain elements that allow us to make this proposal a reality. The project aims to census the classrooms to improve the stay of people who walk through the institution every day, obtain environmental data from the classrooms in real time and manipulate the current that can be delivered to a lamp. In this article, we talk in depth about the construction process of the architecture, in which the whole project will be based in a technical way, but at the same time making it as understandable as possible for any type of public.

A proposal of an architecture is described for the use of intelligent agents connected to a mobile application and the same time is also linked to a control system that is managed by the institution. In this document the idea is analyzed from its conception, through the elaborated development and the tests and the results that have been carried out. This architecture is planned to be used in the creation of an intelligent university campus with data collection, information analysis and automated decision making.

School dropout is one of the biggest problems in the country of Mexico, there are several factors that cause it, so it is necessary to propose strategies and lines of action to reduce it. This document analyzes a database with the demographic and social characteristics of high school students, which were collected through the application of school questionnaires and reports, in order to detect the factors that cause students to drop out of school, as well as to identify in time the students who need personalized counseling to offer them educational guidance and prevent them from dropping out of school, this analysis was implemented through machine learning techniques by developing a predictive model with the gradient descent algorithm, from the results to check the forecast errors by applying the mean square error metric, to estimate the possible prediction errors of the model, it is expected to have a great social impact by applying these machine learning techniques in educational community achieving that students can strengthen their comprehensive training, in addition to guiding their talents and interests.