Conference Agenda

This article presents the design of a Last-Mile Logistics Information System (SILUM), an operational prototype aimed at optimizing the distribution of food supplies in natural disaster scenarios. Through comprehensive modeling using UML diagrams, a four-layer modular architecture was developed, integrating six functional modules: planning, distribution center management, route tracking, delivery confirmation, needs management, and data monitoring. The solution stands out for its operational resilience, employing an offline-first approach with SQLite and VHF radio communication to ensure data synchronization in low-connectivity areas. Implemented in vulnerable districts such as La Molina and Lurín, SILUM proves to be a critical innovation in humanitarian logistics, enabling full traceability through RBAC controls and encryption, reducing response times, and maximizing equity in the delivery of essential resources.

– This work-in-progress research presents the design and technological maturation of a modular food dehydrator optimized for high-altitude Andean environments, transitioning from TRL 4 to TRL 8. The system integrates a hybrid energy matrix consisting of solar photovoltaic, solar thermal, and biomass gasification, coupled with an advanced thermal energy storage unit (thermal battery). The study addresses the critical issue of post-harvest losses in rural communities like Nitiluisa, Chimborazo, where annual agricultural waste exceeds 30%. Through a comprehensive state-of-the-art review and technological surveillance of 139 verified scientific sources and international patents, the paper defines the thermodynamic, structural, and control requirements for 24/7 autonomous operation. Preliminary computational fluid dynamics (CFD) simulations validate internal temperature stability between 40-60°C and a potential CO2 emission reduction of 15% in the first year.

Traditional practices for preheating refractory materials in dental laboratories often yield varying temperatures due to their artisanal construction. The thermal inaccuracy creates defects in the coating cylinders during the injection processes. To address this problem, an automated system is implemented here by proportional-integral-derivative (PID) control to optimize wax preheating and implement special functionality for working with resin. An assessment of the current oven structure was performed, highlighting the structural shortcomings and deficiencies in the thermal control system. To address it, an electronic system was established that comprises a type K thermocouple, a microcontroller, and actuators used for power control, controlled by a PID algorithm adjusted in MATLAB. Two operational modes were proposed, one with a steady thermal ramp up to 950°C for wax and another in two timed stages for resin. The actual conditions (testing in real laboratory conditions) were used to validate the system. Results showed that the thermal variability was reduced to ±0.5°C, and this increased the reproducibility of coating cylinders. The power consumption of the two mechanical processes was improved, with 18% better energy efficiency than the manual process, without surface cracks. Furthermore, the human-machine interface was integrated for immediate observation and data recording for later analysis. Automation increased the precision, reliability, and standardization in thermal processing. The current proposal serves as a model to facilitate optimal heat treatment in dental laboratories with high-quality standards.

Abstract— In the telecommunications sector, efficient management of finished-goods inventory is essential to ensure profitability and operational effectiveness. Through the analysis of a Peruvian company in the industry, the root causes of its low inventory turnover level were identified, reflected in a ratio of 7.48 turns per year—below the sector average of 9.2 annual turns. This outcome is mainly attributed to excess purchasing, immobilized stock, and other operational deficiencies. To reverse this situation, the proposal integrates process standardization and Industry 4.0 enablers, the use of time series to improve forecasting, the combined application of SLP to enhance warehouse layout design, and finally a fuzzy-logic ABC model to increase classification accuracy of items. The objective is to optimize inventory management and improve overall turnover performance.

In university software engineering projects developed using agile approaches, teams often prioritize early delivery of functionality, leaving formal quality assurance and process maturity in the background. This article presents the experience of the SIGEPRO (Academic Advisory Project Management System) project, developed in an advanced university course in Software Engineering with the active participation of a real client. The project began using Scrum as a framework, with a focus primarily on product quality; however, as the system increased in complexity, limitations related to document standardization, traceability, and change management were identified, which led to the gradual incorporation of formal quality assurance practices. These practices focused both on product quality, based on the ISO/IEC 25010 model, and process quality, using guidelines derived from the ISO/IEC 12207 and ISO/IEC/IEEE 15289 standards. The results show a gradual evolution towards a more disciplined and consistent process, with improvements in change management, traceability, and development visibility, without affecting the iterative nature of the agile approach. Experience shows that the progressive integration of agile practices with formal quality standards is feasible and formatively valuable in advanced university contexts, especially when projects involve real clients.

This study presents an analysis of the feasibility of implementing conventional devices (point absorbers, attenuators, and OSWECs) used to convert wave energy into electrical energy at three potential sites in the Republic of Panama (Playa Venao, Santa Catalina, and Punta Burica). This analysis applies to the Panamanian Pacific coastline under five specific points: physical and geographical conditions, ocean behavior under climatic influences, coupling of device operating conditions at the sites studied, electrical interconnection, and protected areas. The objective of this study is to answer the question: Which of the three devices is best suited to the physical conditions of the site to achieve stable generation throughout the year? This will enable us to determine the site with the best operating conditions or whether the implementation of these conventional devices is simply not viable and it is necessary to design a wave energy device that is adapted to the conditions of the Panamanian Pacific.

Panama is facing a scenario in which the energy transition is becoming a reality, and issues such as electric mobility and renewable energy are gaining prominence. Within this context, challenges arise, particularly regarding the management of batteries originating from these applications. Therefore, providing these batteries with a second life emerges as a viable solution. This article presents a comprehensive review of the existing regulatory framework in Panama and focuses on exploring priority applications for batteries derived from their first life cycle. Furthermore, a set of evaluation metrics is established, considering technical aspects such as regulation and level of technological development, as well as others relevant factors including climatic conditions and national relevance

— First, rapid urban growth and rising consumption in Peru have intensified the logistical and public-health challenges associated with municipal solid waste (MSW) management. Moreover, the segregation of recyclable waste is still largely performed manually, exposing operational workers to biological hazards and limiting the efficiency of treatment plants. In this context, computer vision and convolutional neural networks (CNNs) provide promising alternatives for automating waste classification; however, performance often degrades in local deployments when models are trained exclusively on foreign datasets that do not capture the visual characteristics of products in the Peruvian market (e.g., local brands). Accordingly, this work proposes an automatic waste classification system tailored to the Peruvian context using transfer learning techniques. To this end, a hybrid dataset was built by integrating the standard TrashNet database with a new corpus of images of Peruvian household waste. Finally, 20 experimental configurations were implemented and evaluated, comparing deep architectures (ResNet50, Xception) against lightweight models (MobileNetV2) and baseline variants under different optimizers and data augmentation strategies. Preliminary results suggest that domain adaptation through local data significantly increases classifier accuracy, supporting the technical feasibility of intelligent recycling systems for Peru.