Nowadays, the need to monitor different physical variables is constantly increasing and can be used in different applications, from humidity monitoring to disease detection in living beings, using a local or wireless sensor network (WSN). The Internet of Things has become a valuable approach to climate monitoring, daily parcel monitoring, early disease detection, crop plant counting, and risk assessment. Herein, an autonomous energy wireless sensor network for monitoring environmental variables is proposed. The network’s tree topology configuration, which involves master and slave modules, is managed by microcontrollers embedded with sensors, constituting a key part of the WSN architecture. The system’s slave modules are equipped with sensors for temperature, humidity, gas, and light detection, along with a photovoltaic cell to energize the system, and a WiFi module for data transmission. The receiver incorporates a user interface and the necessary computing components for efficient data handling. In an open-field configuration, the transceiver range of the proposed system reaches up to 750 m per module. The advantages of this approach are its scalability, energy efficiency, and the system’s ability to provide real-time environmental monitoring over a large area, which is particularly beneficial for applications in precision agriculture and environmental management.

Several kinds of research conclude that the level of digital competence of students is mainly oriented to their daily activities. Therefore, we present the current paper which seeks to determine the impact of implementing a blended learning course designed to improve digital competence for research (DCR) among a group of undergraduate engineering students. With this approach, a quasi-experimental explanatory methodology with a causal-comparative scope was applied. For this reason, the results were analyzed before and after applying a specially designed course to the experimental group, comparing it with a passive control group by collecting data using three previously validated instruments. For data analysis, students’ t-tests and two-way ANOVA (Analysis of Variance) were used, estimating the effects with Cohen’s study. Given the results, there was a statistically significant improvement (p ≤ 0.05) in their skills and attitudes, but not in their knowledge, obtaining a significant effect size only in the procedural dimension (f = 0.41 y η² = 0.142). Therefore, the implementation of the course used in the blended learning modality is considered to significantly improve the DCR of a group of undergraduate engineering students, although the results should be evaluated with due reservations.

The global water crisis represents one of humanity’s most pressing challenges, with over 2 billion people lacking access to safely managed drinking water. This study presents the implementation and evaluation of an innovative air-conditioning condensate recovery system at Building F of the Faculty of Electrical and Electronic Engineering (FIEE), Universidad Veracruzana, Mexico. The system integrates twenty-six 24,000 BTU air-conditioning units across twelve classrooms and two laboratories, recovering approximately 520 L of condensate water daily. An initial physicochemical characterization of the recovered condensate was conducted through pH, electrical conductivity (EC), and total dissolved solids (TDS) measurements. In addition, the dried residue obtained after evaporation of the condensate was examined using semi-quantitative X-ray fluorescence (XRF) analysis. The XRF results describe the relative elemental composition of the dried residue and must not be interpreted as aqueous concentrations or as evidence of compliance with water-quality standards. The recovery system includes a nominal 0.5 µm polypropylene sediment cartridge, activated-carbon filtration, and a Crystolite^® treatment medium. Because paired measurements before and after treatment were not performed, the removal efficiencies of these components were not determined. The recovered water is subsequently stored and processed in a dual-tank configuration: a primary 3300 L storage system and a secondary 200 L tank used to prepare fertilizer-amended condensate for ornamental-plant irrigation. A fully water-soluble monopotassium phosphate fertilizer (MKP, 0 (–52–34) was incorporated at a gravimetric proportion of 1:10 (1 g MKP per 10 g recovered condensate water).

Este libro presenta una revisión exhaustiva del análisis y aplicación práctica del analizador vectorial de redes NanoVNA S-A-A-2 en el estudio de las líneas de transmisión y circuitos de RF. Destaca su utilidad como herramienta didáctica y de investigación en el aprendizaje y desarrollo de habilidades prácticas en dicha área. Los colaboradores son profesores de la Facultad de Ingeniería Eléctrica y Electrónica y, en su mayoría, integrantes de dos cuerpos académicos actualmente consolidados. La obra aporta una metodología estructurada de validación experimental, que puede ser adoptada para investigaciones y prácticas de enseñanza, para enriquecer la formación en el área de RF a estudiantes y profesionales. Se detalla el paso a paso para la calibración, configuración de montajes y análisis de resultados usando el NanoVNA, lo cual le permite al lector reproducir y adaptar las técnicas en diferentes entornos de laboratorio. Además, se fomenta el aprendizaje activo mediante la resolución de ejemplos prácticos y ejercicios orientados a aplicaciones profesionales y académicas. Entre las principales aportaciones de esta obra frente a otras bibliografías, destaca la integración del equipo NanoVNA S-A-A-2 en un esquema pedagógico asequible y accesible, que facilita el aprendizaje y la experimentación con instrumentos de bajo costo sin sacrificar precisión, fomentando el desarrollo de razonamientos críticos en la resolución de problemas en el área de RF.

Firstly, I would like to congratulate you on the importance of your work. Next, I present a series of recommendations that I would appreciate if you attend to them. • Add more references from 2023, since they only have one. • Section 2 is very extens...