Conference Agenda

This study analyzes the relationship between green infrastructure and the moderation of the surface urban heat island effect in the district of Lince (Lima) through a multitemporal analysis covering the period 2015–2025, based on Landsat 8 and 9 satellite imagery selected annually according to seasonality and radiometric quality criteria, excluding years without suitable image availability. Despite the limited availability of green areas in the district (3.04 m² per inhabitant), a value below commonly cited international recommendations, vegetation associated with urban green infrastructure exhibits a consistent thermal regulatory effect. The processing of bands 4, 5, and 10 enabled the estimation of NDVI, LST (land surface temperature), and UHI (urban heat island intensity) for 5,601 urban units. NDVI values were generally low in the most recent years, ranging from −0.01 (2021, 2023, and 2024) to 0.36 (2018 and 2023), indicating low vegetation cover with localized increases in greenery. LST values ranged from 15.41 °C to 45.40 °C. In addition, critical UHI events of up to +5.48 were identified, while areas with higher vegetation cover exhibited negative thermal anomalies of up to −5.00, demonstrating the mitigating effect of urban green infrastructure on surface heat accumulation. Across the evaluated years, NDVI–LST and NDVI–UHI relationships showed negative and statistically significant correlations (r between −0.595 and −0.480; p < 0.001), indicating that even limited areas of urban green infrastructure are associated with reduced surface heat accumulation in a densely urbanized district such as Lince.

The present study aims to improve environmental management at Curtiembre & Servicios Libertad S.A.C. in Trujillo - La Libertad to reduce its environmental impacts and operating costs. Four main causes of environmental problems were identified: environmental regulatory non-compliance, industrial effluent contamination, inadequate management of hazardous waste, and lack of control of environmental parameters. These problems affected production processes, the environment, and the company's profitability. To address this, an Environmental Management Plan, a Contingency Plan, and a Monitoring and Control Plan were proposed as improvement measures. The implementation of these plans reduced economic loss from S/. 22,500.00 to S/. 4,200.00, resulting in a significant economic benefit for the tannery. The economic-financial evaluation of the proposal showed an NPV of S/. 29,184.39, an IRR of 95.16%, a payback period of 6.90 months, and a Benefit-Cost ratio of 1.6, supporting the economic viability of the proposed improvements.

This work presents a specialized automated monitoring system for hydroponic maize green fodder that addresses key limitations of existing plant disease detection approaches. Unlike prior works focusing on field crops with high-end computing infrastructure, our system operates on low-cost ESP32-CAM hardware while achieving competitive accuracy. The system integrates classical HSV-based segmentation with MobileNetV2 classification, exploiting multiple camera viewpoints (superior and inferior) for enhanced diagnostic reliability. Fixed-size patches (250×250 pixels) extracted from segmented regions serve as input to the binary classifier (healthy/diseased). The network achieved 95.01\% accuracy for superior view and 97.28\% for inferior view, comparable to state-of-the-art approaches using computationally expensive architectures. Key contributions include: (1) specialized preprocessing for hydroponic imaging conditions, (2) edge-compatible deployment maintaining high accuracy, (3) integrated height measurement for comprehensive crop monitoring, and (4) multi-view assessment enhancing diagnostic confidence. The system demonstrates the feasibility of deploying efficient deep learning solutions in resource-constrained agricultural environments.

The main objective of the research was to determine the relationship between the circular economy and competitiveness in a hydrobiological export company. It is in line with Sustainable Development Goal (SDG) 12: Responsible consumption and production, promoting the efficient use of resources and the circular economy to reduce environmental impacts, improve efficiency, lower costs, and strengthen corporate social responsibility, thereby improving competitiveness.
The methodology was applied, with a quantitative approach, a non-experimental cross-sectional design, and a correlational scope. The final sample consisted of 50 workers from a hydrobiological company located in Paita. The results showed that there is a moderate positive relationship between the implementation of the circular economy and competitiveness strategies in a hydrobiological exporting organization, which was statistically determined by a Rho=0.685 (p < 0.01). It was concluded that there is a positive and significant relationship (ρ = 0.685; p < 0.01) between the variables studied, circular economy and competitiveness, in a hydrobiological export company.

The accelerated growth of Data Centers and Cloud Computing has significantly contributed to the increase in global energy consumption and carbon emissions, creating an urgent need to adopt green computing strategies aimed at sustainability. This study conducts a Systematic Literature Review (SLR) with the purpose of identifying and analyzing the most effective strategies for energy optimization and carbon footprint reduction within data center environments. The PICO methodology was used as the basis for the research. A structured search filter was applied in the SCOPUS database, covering the period from 2020 to 2025 and following the guidelines of the PRISMA model. The search initially yielded a total of 244 articles, which were filtered by year, language, and accessibility, and then screened using inclusion and exclusion criteria (focused on the PICO questions). In the end, 52 articles were selected. These articles address key topics such as the use of renewable energy sources, advanced thermal management techniques, virtualization, and intelligent energy optimization algorithms. The results highlight a comprehensive approach that integrates operational effectiveness, technological innovation, and environmental sustainability to improve the energy performance of data centers

This work presents the adaptation of a Bajaj NS 200 cc engine to operate with synthesis gas obtained from biomass using an experimental gasifier. A dual-fuel supply system with an Emmegas vaporizer was implemented, evaluating engine performance with 85-octane gasoline, LPG, and a 95% LPG – 5% syngas mixture. Results show that compared to gasoline, power decreased by 14.9% with LPG and 37.1% with the syngas mixture; while torque decreased by 60.6% and 67.7%, respectively. Despite these reductions, the conversion demonstrates the technical feasibility of using synthesis gas in small displacement engines, opening perspectives for the development of cleaner alternative fuels.