EASI: Volume 4, Issue 2. [Special issue]

Authors

  • Franklin Samaniego-Riera Faculty of Industrial Engineering, Universidad devGuayaquil, Guayaquil 090112, Ecuador.

DOI:

https://doi.org/10.53591/t11qqk22

Abstract

The study and application of AI, together with simulation and prospective models, enable us to tackle new industrial and environmental challenges. Functional prototypes therefore improve efficiency, sustainability, and decision-making in various sectors through innovative, data-driven technological solutions.
Explore articles that inspire simulation and in-depth analysis of new technologies. Immerse yourself in this new work presented by EASI.

Author Biography

  • Franklin Samaniego-Riera, Faculty of Industrial Engineering, Universidad devGuayaquil, Guayaquil 090112, Ecuador.

    Ph. D. in Automation, Robotics and Industrial Informatics, Universitat Politècnica de València, Valencia - Spain, Master's Degree in Computer Science and Technology, Universidad Carlos III - Madrid - Spain, Master's Degree in Robotics and Automation, Universidad Carlos III - Madrid - Spain. Engineer in Electronics and Computer Science, Escuela Superior Politécnica de Chimborazo - Riobamba - Ecuador, Technologist in Applied Computer Science, Escuela Superior Politécnica de Chimborazo - Riobamba - Ecuador. Researcher UPV 2015-2019, University Professor - Escuela Superior Politécnica de Chimborazo (ESPOCH), Universidad Nacional de Chimborazo (UNACH), Universidad de Guayaquil (UG), Pontificia Universidad Católica del Ecuador sede Ambato PUCESA, Secondary School Teacher, Primary School Teacher, Publications in high impact Scientific Journals and International Congresses. General Manager of SAPVA Publishing House.

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Published

2025-11-08

Issue

Vol. 4 No. 2 (2025): [Special issue] CIIA 2025 - International Conference of Applied Industrial Engineering: Intelligent Models and Data Engineering

Section

Editorial

License

Copyright (c) 2025 Franklin Samaniego-Riera

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How to Cite

EASI: Volume 4, Issue 2. [Special issue]. (2025). EASI: Engineering and Applied Sciences in Industry, 4(2). https://doi.org/10.53591/t11qqk22