Dynamic fuzzy model for detecting verbal violence in real time

• Autorzy: Campos Obed , Pancardo Pablo , Hernandez-Nolasco Jose Adan

Identyfikatory

DOI

10.7494/csci.2022.23.4.4616

• Języki publikacji: EN

Abstrakty

EN

The crime rates in Mexico have been increasing in recent years; every day, there are reports on social media and in the news where assaults and verbal aggression by criminals can be seen. Public transportation units suffer from violence that authorities have not been able to reduce despite their efforts. This is why we have developed a fuzzy logic model that can adapt to almost any scenario thanks to the dynamism that we have implemented in each of its stages. We have obtained promising results that we believe will be of great help to the authorities for detecting the exact moment in which verbal aggression that is typical of a violent assault is happening in real time. This is a tool to help the authorities, not a substitution; we are simply making use of the latest technologies that are available to us. The goal of this paper is to provide a novel method for Mexican authorities in Mexico City in order to help the actual surveillance systems make faster decisions about whether violent assaults are happening or not.

Słowa kluczowe

EN

fuzzy logic; dynamic; verbal violence; real time

• Wydawca: Wydawnictwa AGH
• Czasopismo: Computer Science
• Rocznik: 2022
• Tom: T. 23 (4)
• Strony: 467--493
• Opis fizyczny: Bibliogr. 38 poz., rys., tab.

Twórcy

autor

Campos Obed

• Autonomous Juarez University of Tabasco, Academic Division of Science & Information Technologies

autor

Pancardo Pablo

• Autonomous Juarez University of Tabasco, Academic Division of Science & Information Technologies

autor

Hernandez-Nolasco Jose Adan

• Autonomous Juarez University of Tabasco, Academic Division of Science & Information Technologies

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Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).