Conference Agenda

Abstract- This study presents a global systematic review on the effectiveness of renewable energy in reducing greenhouse gas (GHG) emissions, analyzing 39 empirical studies published between 2015 and 2025. Through searches in databases such as Scopus, Web of Science, ScienceDirect, IEEE Xplore, and Google Scholar, relevant studies were identified according to rigorous inclusion and exclusion criteria. The findings confirm that the energy sector remains the largest emitter of GHGs, primarily due to the use of thermal sources and the exploitation of hydrocarbons. However, renewable technologies such as solar, wind, and hydropower have shown high effectiveness in mitigating emissions, especially when integrated with solutions such as Carbon Capture and Storage (CCS). The study highlights key technical challenges, such as intermittency and the integration of these sources into electricity grids. Furthermore, it underscores the importance of public policies—such as carbon taxes and incentives for clean energy—to accelerate the transition to a sustainable, low-carbon energy model. This review provides empirical evidence to the global debate on the strategic role of renewable energy in addressing climate change. Keywords: Renewable energy, Efficiency, Emission reduction, Greenhouse gases, Systematic review.

The objective of the research is to analyze academic integrity in the use of artificial intelligence in university students, for which the scientific literature from the Scopus database was reviewed. For the research, 600 scientific articles were initially evaluated. The PICOT methodology was used to determine the search parameters and research questions, and PRISMA was also used for the ideal selection of articles based on inclusion and exclusion criteria, obtaining in a first filtering 123 articles and in a second, 95 articles, which were reviewed in their entirety. Regarding the results, students perceive the impact of AI on academic integrity both positively and negatively. Likewise, there are various problems that arise such as: plagiarism, dependency, loss of critical skills, lack of AI detection, lack of clear standards, etc. Furthermore, 83.3% consider that AI favors integrity, but is also a threat, so it is necessary to establish clear guidelines based on a culture and ethical training. Keywords-- Artificial intelligence, academic integrity, higher education, ethics.

This research addressed the optimization of video surveillance camera placement using binary programming and graph theory in the Santa Elena neighborhood. In this context, the main objective of this project was to design a mathematical model to determine the optimal placement of video surveillance cameras, in order to maximize coverage of critical points and, consequently, strengthen citizen security. To achieve this, binary integer programming was applied, which allowed for the optimal selection of resources, and graph theory was also used to represent the connections and relationships between vulnerable areas. Furthermore, the research followed a quantitative approach with a non-experimental design, supported by the collection of data on crime rates and the spatial distribution of the neighborhood. As a result, it was evident that the proposal significantly reduced unmonitored areas and optimized resources compared to a traditional scheme, thus ensuring greater strategic coverage with fewer cameras. In summary, it is concluded that the integration of advanced mathematical tools constitutes an effective alternative for planning urban security systems, contributing to both crime prevention and improving the perception of security among the residents of Santa Elena. It is also applicable to other communities with similar problems.

Abstract– The objective of this project was to develop and implement an Automated Bioelectric Garden as a sustainable alternative for generating electricity in rural areas without access to conventional service, focusing on the El Chorro Annex, La Libertad de Pallán district, Cajamarca. The methodology consisted of designing and assembling microbial fuel cells using live succulent plants, zinc and copper electrodes, and silt loam soil, without including energy storage systems. The cells were connected in series and parallel to directly power a

3W LED bulb. Experimental results showed that each plant generated an average of 0.4 volts, which was insufficient to power the bulb; at least six connected plants were required to reach the necessary voltage. Despite not achieving direct ignition, the technical feasibility of the

bioelectric principle and the structural functionality of the system were validated. It is concluded that this technology represents an environmentally friendly, low-cost, and replicable solution, but requires improvements in system architecture, preferential use of zinc as an anode, the incorporation of electrical storage, and community training strategies for its effective and sustainable implementation in vulnerable rural areas.

El objetivo de esta revisión sistemática fue analizar cómo las tecnologías de Blockchain e Inteligencia Artificial (IA) se aplican para mejorar la trazabilidad en la cadena de suministro farmacéutica, identificando sus beneficios y limitaciones. Como método, se aplicó la metodología PRISMA y protocolo PICO (P(Población), I(Intervención), C(Contexto), O(Resultados)) para la búsqueda y selección de artículos en la base de datos Scopus, Web of Science e IEEE Xplire publicados entre 2020 y 2025. Tras filtrar 1731 publicaciones, se seleccionaron 60 estudios para el análisis final. Los resultados demostraron que la integración de Blockchain e IA mejora significativamente la autenticación de medicamentos y la eficiencia logística, con redes neuronales alcanzando precisiones de hasta el 95% en la detección de fraudes. Sin embargo, se identificaron como barreras críticas los altos costos de implementación, los desafíos de interoperabilidad con sistemas existentes y la necesidad de personal técnico especializado. Se concluye que, si bien la combinación de Blockchain e IA posee un enorme potencial para crear una cadena de suministro más segura y transparente, su adopción a gran escala está actualmente limitada por barreras económicas y operativas significativas, revelando una brecha entre la viabilidad teórica y la implementación práctica.

A bibliometric analysis was conducted on the use of nanofluids in solar thermal systems. A total of 753 English-language documents indexed in the Scopus database between 2004 and 2024 were collected. The analysis shows sustained growth in research on the use of nanofluids in solar thermal systems, consolidating it as a dynamic and multidisciplinary field, led by Asia, especially India and China. Institutions such as Shanghai Jiao Tong University and Jiangsu University stand out for their productivity and collaboration. Works such as those by Mahian O., Saidur R., and Taylor R. A. are the most cited and influential, while new authors such as Zafar Said and Jamshed Wasim promote innovative approaches. Frequent keywords such as "nanofluids," "solar heating," and "thermal conductivity" reflect the interest in improving the thermal performance of these systems through the application of nanotechnology. Journals such as Solar Energy and Renewable and Sustainable Energy Reviews are leading the way, and emerging topics in magnetohydrodynamics and nanofluid flow offer new research opportunities.

This study presents a bibliometric analysis on nanofluids applied to cooling systems. The findings reveal a sustained growth in publications between 2009 and 2025, reflecting the growing interest in the development of nanofluids and their use as refrigerants, driven by advances in nanoparticle synthesis and characterization technology, the increasing importance of sustainable methodologies, and the urgency of optimizing the energy and thermal efficiency of refrigeration systems. The bibliometric analysis reveals the dominance of Asian researchers (Kadirgama K, Ramasamy D, Yang L) and countries such as China, India, and Malaysia in scientific production, evidencing regional leadership in thermal applications. The co-occurrence analysis of indexed keywords allowed us to identify current lines of research, highlighting the development of hybrid photovoltaic-thermal systems, thermal management of Li-ion batteries, and heat exchanger optimization. Future projections highlight four strategic axes: consolidation of renewable systems, development of solutions for electronic systems, advances in multiscale modeling, and integration of artificial intelligence for the design of nanostructured materials. These findings underscore the key role of nanofluids in the energy transition, particularly for applications requiring sustainable and efficient thermal management, marking trends toward industrial innovation with a focus on sustainability.