| Resumen |
An intelligent campus has the purpose of improving the quality of life of students, making intensive, global, sustainable and efficient use of information technologies to interconnect all the actors and services for the benefit of the entire community, to establish an intelligent environment of teaching, learning and living[2]. In such smart environments, the role of users is becoming increasingly relevant, going from passive beneficiaries of services to participants assets through their social media activities. In this project, a system for detecting emergency events was developed for the IPN-Zacatenco Intelligent Campus for detecting emergency events, through analyzing messages (tweets) from Twitter users near of the area of interest. Tweets were classified under 4 categories: Mobility, Fire, Health and None (to discard unrelated tweets). In this article, we compare the machine learning models got with the Bayes Multinomial, Vector Support Machines and k-Nearest Neighbors algorithms. © 2020, Springer Nature Switzerland AG. |
