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Platform for Project Management IADESPro, Supported by AI

Sago, Y.Á., Pérez, P.Y.P., Pupo, I.P., et al (2025). Platform for Project Management IADESPro, Supported by Artificial Intelligence. . https://doi.org/10.1007/978-3-031-83643-5_7


Añadido por Pedro Yobanis Piñero Pérez hace 3 días

Platform for Project Management IADESPro, Supported by Artificial Intelligence

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Platform for Project Management IADESPro, Supported by Artificial Intelligence

  • Sago, Y.Á., Pérez, P.Y.P., Pupo, I.P., Herrera, R.Y., Acuña, L.A., Pupo, L.G.H. (2025). Platform for Project Management IADESPro, Supported by Artificial Intelligence. In: Piñero Pérez, P.Y., Pérez Pupo, I., Kacprzyk, J., Bello Pérez, R.E. (eds) Computational Intelligence Applied to Decision-Making in Uncertain Environments. Studies in Computational Intelligence, vol 1195. Springer, Cham. https://doi.org/10.1007/978-3-031-83643-5_7

Abstract

This work addresses the challenges of managing science and innovation projects, with a particular focus on the issues faced by the international science and innovation funding and project management office of CITMA. As part of the study, a state-of-the-art review is conducted to examine trends in project management. A critical analysis based on the literature is then presented. In the methods section, a proposed platform for project management, called IADESPro, is introduced. The proposed platform is based on agile management methods and performance domains, incorporating best practices from PMBOK and ISO standards. The platform is supported by artificial intelligence techniques to aid decision-making. The proposed platform focuses on value generation, covering the various performance domains of project management. In the results section, the implementation of the platform is evaluated in the context of managing research and innovation projects. A comparison is made between the proposed platform and others reported in the literature, with a critical analysis of their advantages and disadvantages. The feasibility of the proposal is demonstrated, along with its potential for decision-making in environments characterized by uncertainty.


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