Vol. 1 No. 1 (2025): Applied Artificial Intelligence: Education, Engineering and Sustainability¶
Articulos
AI in education: how to use it? how to teach it?,¶
- Bello Pérez R, García Valdivia Z, Hernández Cuellar G, García Lorenzo MM, Vázquez Rodríguez R, (2025), “AI in Education: How to Use It? How to Teach It?” AIAS Artificial Intelligence and Applied Sustainability, Vol. 1, No. 1, pp. 19, https://iajournals.uce.edu.do/index.php/aias/article/view/6
Intelligent agent for online teaching of constitutional education, case study¶
Methodology for the development of mobile applications in the desoft matanzas territorial division¶
Explainable artificial intelligence for sustainable development¶
AI-Driven system architecture for enhanced mining project management¶
Proposal for a quality system for a distance learning program in project management.¶
- Pérez Fuentes A., Piñero PérezPY, Alvarado LorcaKJ, Verdecia VicetP,Fustiel ÁlvarezY,(2025). “Proposal for a quality system for a distance learning program in project management”. AIAS Artificial Intelligence and Applied Sustainability, Vol. 1, No. 1., pp. 21, https://iajournals.uce.edu.do/index.php/aias/article/view/10
Framework for digital transformation in logistics management environments assisted by artificial intelligence¶
Ecosystem for Construction of Hybrid Conversational Systems (BRasa)
Mir, Y.O.V., Pupo, I.P., Piñero Pérez, P.Y., Acuña, L.A., Pérez, R.B. (2024). Ecosystem for Construction of Hybrid Conversational Systems (BRasa). In: Piñero Pérez, P.Y., Kacprzyk, J., Bello Pérez, R., Pupo, I.P. (eds) Computational Intelligence in Engineering and Project Management. CIIP 2023. Studies in Computational Intelligence, vol 1134. Springer, Cham. https://doi.org/10.1007/978-3-031-50495-2_8
Abstract
The increasing maturity of artificial intelligence technologies related to conversational systems, such as machine learning algorithms, natural language processing, linguistic data summarization, and natural language generation, is changing the way in which users interact with information systems. In this sense, two trends stand out: the improvement of rule-based smart chatbots and Large Language Models. These two models have different characteristics, with advantages and disadvantages for different scenarios. In this work, the BRasa ecosystem is proposed, which allows the construction of conversational systems that exploit the advantages of the two models. The ecosystem combines different computational intelligence techniques with natural language processing techniques, among which the following stand out: linguistic data summary, fuzzy logic, and neutrosophic theory. As part of the validation of the proposal, using the ecosystem, two conversational systems are built for different environments. The experimental design consists of different tests that demonstrate the applicability and effectiveness of the proposal
Platform as Service for Data Analysis Suppoted by Computational Intelligence Techniques
Ruíz, Y.M., Pérez Pupo, I., Piñero Pérez, P.Y., Acuña, L.A., Vacacela, R.G. (2024). Platform as Service for Data Analysis Suppoted by Computational Intelligence Techniques. In: Piñero Pérez, P.Y., Kacprzyk, J., Bello Pérez, R., Pupo, I.P. (eds) Computational Intelligence in Engineering and Project Management. CIIP 2023. Studies in Computational Intelligence, vol 1134. Springer, Cham. https://doi.org/10.1007/978-3-031-50495-2_7
Abstract
In this work, a cloud-based software architecture for data analysis called BRIntelligent. Its platform allows researchers to perform data analysis by taking advantage of the availability of cloud resources. The proposed architecture constitutes a platform as services that could be extended by groups of researchers based on the development of algorithms and tools for data analysis. With its implementation, it is expected that the end customers of the platform will be able to have access through a web browser to algorithms and data analysis and visualization tools without requiring advanced programming knowledge or installing any specific software. The proposal is structured to consider different architectural views for software development and is made up of three groups of fundamental components. The first component is a data analysis project management system whose functionalities combine computational intelligence techniques and best practices for project management. The second component constitutes a system for the management of algorithm runs, making use of different groups of technological resources. The third component is a set of software assets and services that facilitate data analysis. The proposal has been partially implemented through the customization of the BusinessRedmine software ecosystem using a free software development strategy based on open core.
Combining EDA and Simulated Annealing Strategies in Project Scheduling Construction¶
Piñero Pérez, P.Y., Pupo, I.P., Mahdi, S.S., Quintana, J.M., Acuña, L.A. (2024). Combining EDA and Simulated Annealing Strategies in Project Scheduling Construction. In: Piñero Pérez, P.Y., Kacprzyk, J., Bello Pérez, R., Pupo, I.P. (eds) Computational Intelligence in Engineering and Project Management. CIIP 2023. Studies in Computational Intelligence, vol 1134. Springer, Cham. https://doi.org/10.1007/978-3-031-50495-2_6
Abstract
Project planning can be treated as an optimization problem focused on organizing a set of tasks while respecting a set of precedent constraints and the limited use of renewable and non-renewable resources. The resulting schedule must have the properties of being executed with the least possible time and cost and with a balanced quality of the solution. In this research, a set of new distribution estimation algorithms is presented to solve this problem. Furthermore, the behavior of different evolutionary algorithms in the construction of schedules is compared. The experimental results show the viability of evolutionary algorithms for the agile construction of chronograms and their potential use in BIM environments. In the experimentation, a set of 150 instances collected in 15 databases from the PSPLib library were used. The sensitivity of the behavior of the algorithms is evaluated in the following scenarios: variation in the number of execution modes, in the number of tasks, in the number of renewable resources, and in the number of non-renewable resources, demonstrating the feasibility of the solutions.
Systematic Review of Augmented Reality (AR) and Bim for the Management of Deadlines, Costs and Quality
Acuña, L.A., Rojas, B.H., Reyes, H.P., Arabia, J.H., Piñero Pérez, P.Y., Pupo, I.P. (2024). Systematic Review of Augmented Reality (AR) and Bim for the Management of Deadlines, Costs and Quality. In: Piñero Pérez, P.Y., Kacprzyk, J., Bello Pérez, R., Pupo, I.P. (eds) Computational Intelligence in Engineering and Project Management. CIIP 2023. Studies in Computational Intelligence, vol 1134. Springer, Cham. https://doi.org/10.1007/978-3-031-50495-2_4
Abstract
The BIM (Building Information Management) methodology is widely used today in construction, engineering and architecture. For its part, augmented reality is an emerging technology that has been promoted during the last decade, specifically in the construction industry. Its use has been mainly focused on visualization and virtual construction. This technology has facilitated risk management in projects. In addition, it facilitates collaborative development with clients and project stakeholders. The objective of this study is to carry out a survey of the tools avail-able for the integration and applicability of AR and BIM today. The aim is to re-view the main uses of augmented reality and its integration with other emerging technologies. The technological advantages and limitations of the introduction of these technologies in projects in the industrial and mining sectors in Chile were also reviewed.
Project Scheduling a Critical Review of Both Traditional and Metaheuristic Techniques¶
- Piñero Pérez, P.Y., Pupo, I.P., Mahdi, G.S.S., Quintana, J.M., Acuña, L.A. (2024). Project Scheduling a Critical Review of Both Traditional and Metaheuristic Techniques. In: Piñero Pérez, P.Y., Kacprzyk, J., Bello Pérez, R., Pupo, I.P. (eds) Computational Intelligence in Engineering and Project Management. CIIP 2023. Studies in Computational Intelligence, vol 1134. Springer, Cham. https://doi.org/10.1007/978-3-031-50495-2_3
Abstract
Project planning is a problem usually discussed in the different project management standards as an essential problem to be addressed from the project initiation stage. It is a problem that has traditionally been treated by formal methodologies. But current trends in project development have a greater focus on agile methodologies. This situation causes greater variability in project plans. In the particular case of BIM methodologies, the approach is aimed at achieving the simulation of the production process through virtual construction. In this context, in this work, a critical analysis of different approaches that deal with the construction of project schedules is carried out. In particular, the problem is analyzed from a hybrid perspective. The approach proposed by project management standards and the approach to scheduling problems raised by computer science are analyzed. As a result of the analysis, a group of lines open to research are proposed that combine traditional tendencies with metaheuristics.
Fuzzy Cognitive Maps, Extensions and Applicability as an Explanatory Artificial Intelligence Model¶
Ruiz, Y.M., Piñero Pérez, P.Y., Pérez Pupo, I., García Vacacela, R., Al-Subhi, S.H.S. (2024). Fuzzy Cognitive Maps, Extensions and Applicability as an Explanatory Artificial Intelligence Model. In: Piñero Pérez, P.Y., Kacprzyk, J., Bello Pérez, R., Pupo, I.P. (eds) Computational Intelligence in Engineering and Project Management. CIIP 2023. Studies in Computational Intelligence, vol 1134. Springer, Cham. https://doi.org/10.1007/978-3-031-50495-2_2
Abstract
The growth of the prediction capabilities of deep neural networks constitutes one of the elements that has allowed the generalization of these models to dissimilar problems. But in the particular case of decision-making in project management, in addition to the quality of the prediction, it is necessary to know the explanation of the responses. This aims to increase the confidence of the systems in decision-making and agility in project management. The explanation of the answers is also important during project cuts, a process that manifests itself as a multistage sequential decision-making problem. In this research, it is proposed to explore the potential of fuzzy cognitive maps and their extensions, considering the potential of these techniques to represent causal relationships. To carry out this work, a conceptual theoretical framework is developed based on a systematic review. It is identified that there are insufficiencies in the research reported in the bibliography consulted regarding the treatment of indeterminacy and the solution of decision-making problems in project managemen
Conversational Systems and Computational Intelligence, A Critical Analysis
Mir, Y.O.V., Piñero Pérez, P.Y., Pupo, I.P., Acuña, L.A., Pérez, R.B. (2024). Conversational Systems and Computational Intelligence, A Critical Analysis. In: Piñero Pérez, P.Y., Kacprzyk, J., Bello Pérez, R., Pupo, I.P. (eds) Computational Intelligence in Engineering and Project Management. CIIP 2023. Studies in Computational Intelligence, vol 1134. Springer, Cham. https://doi.org/10.1007/978-3-031-50495-2_1
Abstract
The increase in research on conversational systems and their applications, constitutes the main motivation of this work. In this research, a critical analysis of the growth of smart chatbots and their combination with computational intelligence techniques is carried out. The analysis is oriented on three fundamental fronts. First, a review protocol is applied to identify the main schools and centers of knowledge. Then the conversational systems are characterized based on the level of inclusion of artificial intelligence techniques. Finally, the integration of conversational systems with different computational intelligence techniques is reviewed. The analysis identifies that there are many opportunities and lines open to research. In particular, the need to strengthen the application of neutrosophic theory and sets for the evaluation of conversations is identified. Also, the need to combine linguistic data summarization techniques and reinforcement learning is identified to improve training methods and reduce the computational cost of conversational systems responses.
Computational Intelligence Applied to Decision-Making in Uncertain Environments
- Pérez, P. Y. P., Pupo, I. P., Kacprzyk, J., & Pérez, R. E. B. (Eds.). (2025). Computational Intelligence Applied to Decision-Making in Uncertain Environments. Springer Nature Switzerland
http://cidiia.uce.edu.do/projects/cidiia-noticias/wiki/Computational_Intelligence_Applied_to_Decision-Making_in_Uncertain_Environments_(2025)_Springer
This book is dedicated to all those interested in the application of computational intelligence techniques for decision-making in uncertain environments. The book is organized into four parts. The first part groups together four works related to conversational systems and decision-making using generative artificial intelligence. The second part includes four articles associated with decision-making in project-oriented environments. The third part includes three works related to decision-making in human health environments and decision-making in sports training. The fourth part of the book contains three articles associated with business decision-making.
This book combines different artificial intelligence techniques for solving decision-making problems, among which the following stand out: generative artificial intelligence, linguistic data summarization techniques, neutrosophic theory, computing with words, among other techniques. The techniques proposed in the book aim to simulate human tolerance in decision-making processes in environments with uncertainty and imprecision.
The authors of the book stand out for their extensive experience in the development of basic and applied applications of computational intelligence. The authors Pedro Y. Piñero Pérez, Iliana Pérez Pupo, Janusz Kacprzyk, and Rafael E. Bello Pérez have published several books associated with artificial intelligence and applied computational intelligence. They continue to work on fundamental and applied research on different artificial intelligence techniques to assist decision-making in different areas of knowledge.
The authors thank all the engineers, professors, and researchers without whose efforts this book could not have been written.
