Main Tools of Artificial Intelligence for Industries : A Literature Review
Descripción del Articulo
The aim of this text is to simplify the analysis of various bibliographic sources that address the use of artificial intelligence in different industrial sectors. The PRISMA methodology was employed to examine articles published in different journals indexed in high-prestige databases that deal with...
| Autores: | , , |
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| Formato: | artículo |
| Fecha de Publicación: | 2024 |
| Institución: | Universidad La Salle |
| Repositorio: | Revistas - Universidad La Salle |
| Lenguaje: | español |
| OAI Identifier: | oai:ojs.revistas.ulasalle.edu.pe:article/154 |
| Enlace del recurso: | https://revistas.ulasalle.edu.pe/innosoft/article/view/154 https://doi.org/10.48168/innosoft.s16.a154 https://purl.org/42411/s16/a154 https://n2t.net/ark:/42411/s16/a154 |
| Nivel de acceso: | acceso abierto |
| Materia: | Artificial intelligence tools, artificial intelligence tools for industries, industries Herramientas de inteligencia artificial, herramientas de inteligencia artificial para industrias, industrias |
| Sumario: | The aim of this text is to simplify the analysis of various bibliographic sources that address the use of artificial intelligence in different industrial sectors. The PRISMA methodology was employed to examine articles published in different journals indexed in high-prestige databases that deal with the use of AI tools in these areas. An exhaustive literature review was conducted in Scielo and Scopus to ensure the inclusion of a broad spectrum of relevant research. This extensive review allowed for the identification of significant trends in the use of artificial intelligence in different geographical regions and specific industrial sectors. It was observed that countries such as the United States, Brazil, and Colombia stand out for their leadership in the production of articles related to AI in their respective industries. Likewise, it is noted that AI tools, such as neural networks, ChatGPT, chatbots, and machine learning, not only optimize industrial processes but are also driving disruptive innovations in areas such as computer science, engineering, social sciences, business, management, accounting, chemical engineering, medicine, and materials science. This exhaustive analysis provides a solid and informed basis for strategic decision-making and guides future research aimed at maximizing the potential of artificial intelligence in the industrial field. |
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Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).