The purpose of this study is to summarize the pattern recognition (PR) and deep learning (DL) artificial intelligence methods developed for the management of data in the last six years. The methodology used for the study of documents is a content analysis. For this study, 186 references are considered, from which 120 are selected for the literature review. First, a general introduction to artificial intelligence is presented, in which PR/DL methods are studied and their relevance to data management evaluated. Next, a literature review is provided of the most recent applications of PR/DL, and the capacity of these methods to process large volumes of data is evaluated. The analysis of the literature also reveals the main applications, challenges, approaches, advantages, and disadvantages of using these methods. Moreover, we discuss the main measurement instruments; the methodological contributions by study areas and research domain; and major databases, journals, and countries that contribute to the field of study. Finally, we identify emerging research trends, their limitations, and possible future research paths.

In this work, we integrate the concepts of Industry 4.0, smart manufacturing, and sustainable manufacturing in a model that provides a conceptual framework for the study of long-term solutions with a high degree of specialization, according to the specific context of each investigation. This study offers a holistic analysis and evaluation of the main challenges facing the Industry 4.0 concept. We also diagnose the current methodological proposals aimed at solving the challenges of Industry 4.0 and sustainability using a systemic review of the literature from the past 5 years. Firstly, we identify 14 technological trends linked to Industry 4.0. Subsequently, the trends are integrated into the proposed model to identify opportunities, evaluating their relationship with three performance areas. This allows the identification of trends that present the greatest number of opportunities in the context of sustainability. The second stage complements the literature review with a descriptive analysis of the studies and discusses the findings. The study concludes that the identified technological trends positively impact Industry 4.0 challenges, helping to achieve sustainable manufacturing objectives.

Blockchain technology (BC) offers an innovation platform for decentralized and transparent transactions in the maritime port industry. This technology allows guaranteeing trust, transparency and traceability of cargo and data to be tracked. Today, in the port systems of emerging market countries, BC technology is increasingly being incorporated into information and communication processes. In parallel, the social domain has begun to be explored due to the lack of link between the port and the city it occupies, and the need to incorporate public actors in decision-making at the governance level. In this sense, the present work aims to promote BC technology in order to transform data and information into useful knowledge for effective decision making, through the use of Crowdsourcing. A Crowdsourcing Blockchain CrowdBC conceptual framework and its architecture are generated for a port system in which the cyber-technological, social and cognitive domains (CSTC) of smart ports, the knowledge generation process and Crowdsourcing technology are interrelated. Finally, opportunities are discussed for ports that are in permanent development to reduce the gaps with the smart industry. As a discussion, two possible scenarios and recommendations for future implementations that consider the social and cognitive aspects of Industry 4.0 are presented.

This research investigates the optimal integration of Blockchain Technology (BT) in Supply Chain Management (SCM) within Chile’s maritime ports. Utilizing fuzzy Logarithmic Methodology of Additive Weights (LMAW) and Double Normalization-based Multiple Aggregation Methods (DNMA), the study systematically identifies, prioritizes, and ranks key factors influencing BT adoption in SCM. The study’s findings highlight crucial factors like enhanced transaction security, good supply chain practices, and risk management. Furthermore, it ranks the application of ports as prime candidates for BT integration. The research contributes theoretically by developing a hybrid model combining MCDA methods, and practically by guiding the strategic application of BT in the maritime logistics sector, aligning with the principles of Industry 5.0. This paper presents a novel approach that explores the utilization of BT in maritime supply chain management, incorporating MCDA in a vague environment. The research gap of this study lies in defining new contexts in both theoretical and practical literature reviews for extending the use of BT in SCM in the ports of Chile, according to Industry 5.0, to increase the efficiency and effectiveness of all aspects of operations in these places. The contribution of this research is applying hybrid MCDA methods in an uncertain environment to assist decision-makers (DMs) in better implementing BT in SCM in Chilean ports, according to Industry 5.0.

This article reviews studies on the application of reverse logistics in solid waste from the construction industry. The main objective is to provide a summary of current knowledge and specific areas for future research. In addition, construction, as an economic sector, is in a continuous search for new tools to improve its processes, so this research provides the current situation of the relationship between reverse logistics and solid waste in the industry. The review methodology was content analysis of scientific literature published between 1997 and 2020, and total of 66 articles were used. 73% correspond to research articles, around 13% are case studies, and 12% are literature reviews. Only one of the articles is a survey. In addition, 52% of the works reviewed correspond to solid waste studies and 49% are related to the construction industry; only one publication does not classify in any. The most used keywords for the identification of published works were reverse logistics and supply chain; both terms are frequently related to the process and general management of solid waste and construction. The least used term was the literature review that shows the low number of articles that provide a summary of the proposed topic. Finally, three materials were chosen for the study because they are the most used in construction: metals, bricks, and concrete. 15% of the articles study all three, 18% study only metals, and 63% study other materials or are related to construction and solid waste in general.

The core problem of a multimodal transportation system is integrating various transportation modes into a cohesive, efficient, and user-friendly network. This study introduces a novel centralized load concentration approach for regions facing geographic challenges. The principal aim is improving multimodal transportation systems by mitigating CO₂ emissions and improving operational efficiency. This will significantly reduce high logistics costs and the environmental impact caused by greenhouse gas emissions, particularly in land transportation, aligning with the global sustainable development goals and offering a promising path towards a more sustainable future. The proposed method implicates direct cargo transportation from its origin to the export ports without passing through intermediate centers. The mathematical model determines the most efficient means of transportation for each route, considering variables such as distance, volume, and type of cargo. Research results indicate that multiple hubs may not be necessary in scenarios with high freight concentration, which could streamline transportation and logistics operations. The modal preferences vary depending on regional dynamics and cargo characteristics, with rail and sea transport emerging as preferable options in specific circumstances, outperforming road transport. The proposed model shows reductions in logistics costs and CO₂ emissions compared to road-focused scenarios. This study provides an adaptable framework for optimizing multimodal transportation systems in regions with similar geographic and logistical attributes. It offers a versatile solution to various contexts and needs. Lastly, the strategic integration of multiple modes of transportation is fundamental to improving efficiency and sustainability.