COLOMBIAN JOURNAL OF ADVANCED TECHNOLOGIES
The Colombian Journal of Advanced Technologies aims to disseminate high-impact research in advanced technologies, covering areas such as Telecommunications, Control and Automation, Mechatronics, Artificial Intelligence, Robotics, Power Electronics, Digital Signal Processing, Bioengineering, Software Engineering, Electrical Engineering, and more. It is oriented to be a reference channel for the exchange and development of scientific knowledge, contributing to the advancement of engineering and technology. Published semiannually with national and international coverage, the journal provides a space for knowledge exchange among academics and researchers. In addition to original articles, the journal will publish reviews that examine the state of the art and suggest future directions in developing fields. Manuscripts must be submitted in both Spanish and English for peer evaluation. The editorial management is led by the Vice-Rectorate for Research at the University of Pamplona, under the direction of Ph.D. Aldo Pardo García, with an editorial board of international experts. Indexing: Latindex, Publindex, Dialnet, DOAJ, Redalyc, EBSCO, Google Schoolar, Otros. Frequency: Biannual. Print ISSN: 1692-7257, Online ISSN: 2500-8625 Publindex Category: B
Automation of environments in greenhouses simulating future scenarios
This paper presents a study of different types of climate change research stations, where the behavior of different crops under various CO2 concentrations, temperature, and humidity levels, as well as soil changes, are investigated. A possible design of a research station using Intouch, with an interface to a PLC where a SCADA system is implemented, is presented.
Copyright (c) 2017 Aldo Pardo García, Leonidés Castellanos González https://creativecommons.org/licenses/by-nc/4.0
Use of virtual environments and project-based learning for teaching industrial costs: UFPS case study
This article evaluates industrial engineering students’ perceptions of the teaching strategies used in the Industrial Costs course, comparing the Problem-Based Learning (PBL) methodology and case studies with other complementary strategies, highlighting strengths, weaknesses, and opportunities for improvement. The study employed a quantitative, descriptive, non-experimental cross-sectional design, using a 16-item Likert-type questionnaire with five rating levels. The sample consisted of 45 students who took the course during the second semester of 2023 and the first semester of 2024, applying PBL as a learning strategy. Data were collected online through Google Forms, and frequency, percentage, and measures of central tendency were analyzed. The instrument was structured into two dimensions: (1) PBL and case studies (10 items) and (2) complementary strategies (6 items). The results show high mean scores for PBL, identifying it as a motivating and high-performance strategy, and recommending it as the core approach of the course.
Copyright (c) 2025 Raquel Irene Laguado Ramirez https://creativecommons.org/licenses/by-nc/4.0
Evaluation of the degree of implementation of Industry 4.0 technologies in metalworking SMEs using the IMPULS maturity model
This study evaluates maturity in the digital transformation of SMEs of the metalworking sector in Boyacá, Colombia, using the promotion model. With a sample of 24 SMEs, a questionnaire was applied to analyze six key dimensions of digitalization. The results show that 83% of the companies are at initial maturity levels, and only 16.4% reaches a level of beginners. The main barriers identified are the lack of financial resources, poor digital infrastructure and low data -based services integration. To move towards a sustainable and competitive digital transformation, it is essential to strengthen digital strategies, human talent and technological infrastructure.
Copyright (c) 2025 Hugo Fernando Castro Silva, Marling Carolina Cordero Díaz, Cristian Camilo Chaparro Serrano https://creativecommons.org/licenses/by-nc/4.0
Digital substations: driving sustainability and cybersecurity in the power sector through emerging solutions
The digitalization of electrical substations, guided by the IEC 61850 standard, is a key pillar in modernizing power grids toward more sustainable, efficient, and secure systems. This article examines the role of digital substations and the impact of emerging technologies, including Software-Defined Networking (SDN), Blockchain, machine learning (ML), and Network Function Virtualization (NFV), in enabling automation, real-time analytics, and resilience against cyber threats. It addresses the challenges of implementation, including the interoperability of legacy systems, cybersecurity risks, and modernization costs, particularly in emerging economies. The paper also explores opportunities for developing more decentralized and intelligent power networks, with Colombia highlighted as a reference case. The analysis provides a comprehensive view of both the barriers and advantages of these technologies in the transition toward digital, interoperable, and resilient electrical infrastructures.
Copyright (c) 2025 Oscar Andrés Tobar Rosero, Luis Fernando Quintero Henao, Ernesto Pérez González https://creativecommons.org/licenses/by-nc/4.0
Design of an automated system for temperature and humidity control in a Pleurotus Ostreatus mushroom culture cell
This article presents the results obtained in a culture cell through the automated management and control of temperature and relative humidity, variables relevant to the quality of Pleurotus Ostreatus mushroom cultivation, in such a way as to minimize the impact of climate and ensure a quality product for consumption. The article describes the engineering process applied to obtain the control system that interacts with the cell, as well as the results obtained by comparing the control group under normal environmental conditions with the culture that uses technology supported by the Internet of Things (IoT)
Copyright (c) 2025 Edgar Rodrigo Enríquez Rosero, Gabriel Andrés Obando Obando https://creativecommons.org/licenses/by-nc/4.0
Sign language to text translation using Python with LSTM neural networks
There is a difficulty that deaf people with speech disabilities face in communicating effectively with those who do not know sign language. Despite the existence of methods such as writing and lip-reading, these have limitations and are not always effective. The proposed solution includes developing a real-time sign language recognition system using convolutional neural networks and the MediaPipe platform. It detects and classifies the positions of hand points to identify letters. Gestures made in front of the camera are translated into letters that are stored to form paragraphs in a text box. The type of research is quantitative and experimental. Ultimately, the importance of sign language recognition and teaching is highlighted, especially in countries such as Colombia, where it has received significant recognition.
Copyright (c) 2025 Luis Duván Torrado Mora, César Alberto Collazos, Dewar Rico Bautista https://creativecommons.org/licenses/by-nc/4.0
Implementation of a Real-Time Pressure and Tilt Angle Monitoring System for Mast Hoisting in NOV Rapid Rig 13 Equipment
This paper presents the implementation of a real-time monitoring system for mast hoisting operations in NOV Rapid Rig 13 equipment, using a distributed architecture with local data acquisition, processing, and visualization layers. The system simultaneously records hydraulic pressure and angular inclination data, enabling analysis of the dynamic behavior of hydraulic cylinders during hoisting operations. This data generated a static pressure curve to correlate pressure and inclination, representing the theoretical model of a three-stage hydraulic cylinder. This curve identified critical transitions and operational deviations, serving as the basis for defining alarm thresholds and enhancing operational oversight—empowering operators to make informed, safety-driven decisions. The results improve hoisting safety and establish a foundation for future automation and predictive maintenance strategies in hydraulic systems applied to drilling operations.
Copyright (c) 2025 Elkin Adoniz Mora Castañeda, Oscar Javier Suarez Sierra, Rocco Tarantino Alvarado https://creativecommons.org/licenses/by-nc/4.0
Voice Driven UML Modeling System for Visually Impaired Students in Software Engineering Education
Visual impairment limits students' access to object-oriented modeling environments that rely on graphical interfaces. Advances in Text-to-Speech (TTS) and Speech-to-Text (STT) technologies make it possible to consider mechanisms to compensate for this barrier, yet their adoption in educational platforms lacks evidence-based guidelines. This work aims to design, implement, and validate a voice-controlled UML modeling system that enables visually impaired students to create, edit, and query class and use-case diagrams. A four-phase methodology was followed: (i) requirements elicitation; (ii) modular architectural design with grammatical validation and the use of large language models (LLMs); (iii) implementation in Python 3.11, FastAPI, and cloud-based STT/TTS services; and (iv) technical evaluation using recognition accuracy, latency, and task-time metrics. The prototype executed 20 critical commands with a recognition accuracy of 97% and maintained full syntactic coherence in the UML models generated. The average times to complete creation, editing, and navigation tasks were 4.23 s, 6.78 s, and 5.24 s, respectively. The average TTS latency (1468 ms) exceeded the 500 ms target, identifying the NLP module as the main bottleneck. The system demonstrates technical feasibility and adheres to the defined accessibility guidelines (WCAG 2.2). Future improvements will focus on reducing TTS latency, expanding the command repertoire, and conducting large-scale usability evaluations (SUS).
Copyright (c) 2025 Carlos Henriquez Miranda, Malak Andres Sanchez Cataño, German Sanchez-Torres https://creativecommons.org/licenses/by-nc/4.0
Modal propagation analysis in waveguides for the design of evanescent wave photonic biosensors
This paper presents a modal propagation analysis of Strip and Rib waveguides with silicon and SU-8 cores, aimed at designing evanescent wave photonic biosensors. The objective was to determine structural configurations that optimize device sensitivity, focusing on single-mode and bimodal operating conditions. The study was conducted through numerical simulations using the Finite Element Method in COMSOL Multiphysics. Various combinations of materials, core heights of 220 and 600 nm, and operating wavelengths of 633 and 1550 nm were analyzed to evaluate the behavior of TE and TM propagation modes and the variation of the effective refractive index with respect to the waveguide width. The main outcome is a design table summarizing the optimal core width ranges for each configuration, serving as a practical tool for developing highly sensitive and manufacturable biosensors. Additionally, the presented methodology can be applied to the design of integrated photonic circuits in diverse fields such as telecommunications and optical computing.
Copyright (c) 2025 Jesús Álvarez Guerrero, Jhon Jairo Vejar Caballero, Byron Medina Delgado, Jhonattan Córdoba Ramírez, Ferney Orlando Amaya Fernández https://creativecommons.org/licenses/by-nc/4.0
Wifish: IoT and cloud computing-based aquaculture monitoring platform with AES-128 encryption
The primary objective of this research is to enhance aquaculture management by developing an intelligent system that overcomes the inefficiencies of traditional water quality monitoring. This study introduces and validates WiFish, a comprehensive solution designed for real-time supervision of aquatic parameters across various scales of operation, from small test aquariums to large commercial fish farms. The methodology is founded on an Internet of Things framework, utilizing ESP32 microcontrollers integrated with high-precision sensors to continuously measure water pH, temperature, and salinity. All collected data is secured with AES-128 encryption and transmitted via Wi-Fi to a Huawei Cloud DataArts Studio infrastructure for advanced processing, storage, and analysis. Remote access for monitoring and alerts is provided through a custom mobile application and a Telegram bot. Empirical testing in operational aquaculture environments yielded significant results, demonstrating a 98 percent accuracy rate in measurements. The system's implementation led to a 75 percent reduction in the need for manual supervision and an optimization of resource consumption, including a 30 percent decrease in feed and chemical usage. The principal benefit is that WiFish represents a scalable, secure, and highly effective platform that boosts productivity and promotes sustainability. It successfully proves that integrating secure cloud computing and Internet of Things technology can profoundly transform water resource management in the modern aquaculture industry.
Copyright (c) 2025 Andrés Joshue Cuenca Luna, Rony David Quelal Villarreal, Fabricio Sebastián Donoso Martínez, Fabián Geovanny Cuzme Rodríguez, Pablo David Muñoz Criollo https://creativecommons.org/licenses/by-nc/4.0
Digital tool to optimize audits based on the ISO/IEC 27001:2022 standard
This article presents an applied research study focused on the design, development, and validation of SECUREISO, a digital tool aimed at optimizing audit processes in information security management systems aligned with the ISO/IEC 27001:2022 standard. The study employed an agile methodological framework (Scrum), combining secure development practices with empirical validation techniques, including automated penetration testing using OWASP ZAP and the Technology Acceptance Model (TAM). Results demonstrate levels of usability, perceived usefulness, and operational efficiency. Furthermore, its flexible and scalable architecture enables adaptation to diverse sectors. This work contributes to the cybersecurity field by offering a replicable, research-based solution that enhances standard implementation and opens new avenues for investigation in automated digital auditing.
Copyright (c) 2025 Sebastian Buesaco, Alejandro Alcaraz Gaviria, Juan José Caiza Narváez, Katerine Marceles Villalba, Siler Amador Donado https://creativecommons.org/licenses/by-nc/4.0
Industrial control through reinforcement learning
In this article, the implementation of the flow control technique with artificial intelligence (DDPG) is presented in a fully instrumented functional prototype with industrial sensors and actuators, simulating flow recirculation through three tanks. The methodology used for process identification (first-order plus dead time model (FOPDT)) through ClientServer OPC communication with Matlab® is presented. The design of the reinforcement learning algorithm and its adaptation in the learning environment with experimental data are also presented. The simulation results were satisfactory compared to traditional control techniques, demonstrating robustness against forced disturbances. Finally, the implementation of reinforced learning control integrating TIA Portal and Matlab (trough a PLC-S7-1500 controller) was evaluated with a reference of 600 l/h, achieving 0% overshoot with a settling time of 22s. Compared to other control systems, a better response in settling time and overshoot-free control was observed. Finally, perturbations were applied to the system, observing their effect in relation to the flow.
Copyright (c) 2025 Yessica Cindy Vannesa Mora Cubides, Daniel Steven Arias Otálora, José Antonio Tumialan Borja, Hugo Fernando Velasco Peña https://creativecommons.org/licenses/by-nc/4.0
Method for asbestos detection in hyperspectral images based on the approximate components of the wavelet transform and spectral differential similarity
Considering that one of the challenges in material detection within the field of hyperspectral imaging, given its high dimensionality, is the identification of more computationally efficient methods, this article proposes a method for asbestos detection based on the use of the approximate components of the wavelet transform and spectral differential similarity. Variants of the proposed method were implemented using open-source libraries, including Spectral, PyWavelets, NumPy, Pandas, and Matplotlib, achieving similar effectiveness in asbestos detection compared to the correlation-based method. Furthermore, in terms of computational efficiency, it was found that the three variants of the proposed method were more efficient than the correlation-based method, with the method based on the first component of the wavelet transform yielding the best results, being 13.964% more efficient. Based on these results, the variants of the proposed method can be considered as alternatives to conventional methods, allowing them to be integrated into systems for the analysis and monitoring of asbestos and other materials using hyperspectral images. Additionally, this study demonstrated the feasibility of using open-source tools and libraries for material identification in hyperspectral images, making this research a reference point for research centers and universities to replicate and adapt these methods in remote sensing-based investigations.
Copyright (c) 2025 Gabriel Elías Chanchí Golondrino, Manuel Saba, Manuel Alejandro Ospina Alarcón https://creativecommons.org/licenses/by-nc/4.0
Multi-agent system focused on distributed artificial intelligence processes for order capture and routing
This paper presents the design of a multi-agent system focused on text-operated distributed artificial intelligence processes that works following a dialog model, oriented to the efficient management of industrial product orders. This system integrates five reasoning and action agents: the general agent powered by Google's Gemini artificial intelligence language model that carries the conversation flow and redirects the tasks to the other agents, an agent that identifies customers, an agent that recognizes the products, an agent that generates the orders and an agent that routes. The multi-agent system is designed to interact virtually and conversationally with users, facilitating order creation and management through an innovative approach that integrates advanced natural language processing technologies, vector and relational databases, and optimization methods. Finally, for its validation in a real environment, data from a company that produces and distributes cleaning products are used, allowing the development of different tests for the identification of customers, products, quantities and the establishment of order delivery routes. It is concluded that the conversational flow and techniques used allow users to make queries about customers with an average accuracy of 77.38% and about products with an average accuracy of 88.57%, even in scenarios with semantic ambiguities, managing orders in an intuitive way. It is also possible to optimize order routing by simultaneously considering two criteria that can be weighted: customer importance and distance traveled.
Copyright (c) 2025 Anny Astrid Espitia Cubillos, Robinson Jiménez-Moreno, Mateo Andrés Pulido Aponte https://creativecommons.org/licenses/by-nc/4.0
Design of an electric propulsion system for a subway-type means of transport
This document presents the design of an electric propulsion system for a metro-type transport. For this design, a route was proposed that evaluates the energy demand of passenger mobility in the city of Villavicencio (Colombia). The foregoing allows choosing the technical characteristics necessary to satisfy the quality of the service provided. For this, a mathematical model of the longitudinal dynamics of the vehicle was exposed, which studies the forces of interaction through Gillespie simulation, obtaining relevant information on its behavior compared to its operation, the above is determined by means of a computer simulation. The energy study performs the reading of the altimetry data of the chosen route, together with the inclination angles, through the variation of heights and distances. The simulated simulation executes the different data of the chosen train together with its respective trailer, following the trajectory of the chosen route, in order to quantify the forces, power and energy necessary to carry out the total route.
Copyright (c) 2025 Walter Naranjo Lourido, Danna Alejandra Ávila Cohecha, Yand David Quevedo Turriago, Javier Eduardo Martinez Baquero https://creativecommons.org/licenses/by-nc/4.0
Inverse kinematics for a 2R planar robot based on a neural network with synthetic data through a model ensemble approach
This article presents the development of a neural network-based model, trained with synthetic data, to replace the geometric inverse kinematics of a 2R planar robot. This approach aims to simplify the implementation of kinematics, reducing development time and computational resource usage. The model was created in Google Colab (Python) using TensorFlow/Keras, which facilitated its creation and training. Furthermore, the system integrates real-time image processing to recognize and follow contours, which the robot subsequently traces. A linear and vertical motion was implemented using a rack-and-pinion mechanism, enabling discontinuous tracing between contours of an image. The results, averaging three neural network models, show high accuracy in predicting the angles of the robot's first two joints, with an RMSE of 0.2293 and 0.0739 compared to the geometric inverse kinematics.
Copyright (c) 2025 Angie Paola Mancipe García, Nicolás David Barrera Fonseca, Jorge Eduardo Cote Ballesteros, Jhon Edisson Rodríguez Castellanos, Fabián Barrera Prieto https://creativecommons.org/licenses/by-nc/4.0
Development of an advanced flight training simulator for the c-130H aircraft: an approach to optimizing training capabilities for the Colombian Aerospace Force
The research project focuses on the design, development and implementation of an Advanced Training Device (AATD) for the C-130H Hercules aircraft, key for the Colombian Air Force in tactical, humanitarian and rescue missions. This simulator seeks to reduce dependence on external equipment, optimize resources and costs, and improve local training through training adapted to national scenarios. The AATD integrates advanced technologies, such as XPlane 12, Air Manager and Immersive Calibration, and is designed to replicate real flight conditions, develop critical skills and ensure operational safety. Its methodology includes conceptual design, software and hardware development, testing and implementation, achieving intensive and effective training for pilots and technicians. In addition, it fosters technological innovation within the Air Force, consolidating its preparation to face diverse operational situations with efficiency and competence.
Copyright (c) 2025 George Mauricio Ardila Marulanda, Juan Manuel Prieto Bohórquez, Paula Rocío Macías Castillo, Edwin Alexander Casallas Moreno, María Betzabe Rubiano Esmeral https://creativecommons.org/licenses/by-nc/4.0
Artificial intelligence-assisted innovation in higher education: an analysis of key trends and future directions
The study analyzed the trends and challenges of AI-assisted educational innovation in global higher education through a bibliometric analysis of 666 Scopus documents (2020-2024). The results revealed exponential growth in scientific production, led by China (166 documents) and the US (61), with dominant thematic clusters in AI technologies, pedagogical innovation, and ethics. However, gaps in equity, interdisciplinarity, and longitudinal assessment were diagnosed. Furthermore, international collaborations showed asymmetries, while the explored sources pointed to a low integration of critical perspectives and vulnerable contexts. It is concluded that adopting intelligence in higher education requires solid ethical frameworks, inclusive approaches, and policies that prioritize innovation focused on social justice.
Copyright (c) 2025 Carlos Alberto Gómez Cano, Verenice Sánchez Castillo, Elvia María Jiménez Zapata https://creativecommons.org/licenses/by-nc/4.0
Passive and customized standing technologies: a bibliometric analysis of their global development and contributions from Latin America
This article presents a bibliometric analysis of the scientific landscape surrounding passive and anthropometrically personalized standing technologies, with a focus on their global evolution and the notable lack of contributions from Latin America. Based on a systematic review of 435 peer-reviewed articles indexed in Scopus, IEEE Xplore, and Google Scholar between 2010 and 2025, the study applied thematic, geographic, and anthropometric customization filters. Findings indicate a highly concentrated body of research in Asia and Europe, with leading contributions from the University of Tsukuba and EPFL. Moreover, the analysis reveals a persistent gap in integrative approaches that bridge technical design with user-specific adaptation. No Latin American publications met the combined inclusion criteria, highlighting the urgent need to establish a regional research agenda aimed at developing accessible, user-tailored, and contextually relevant assistive standing technologies that address the region’s specific ergonomic and socio-cultural demands.
Copyright (c) 2025 Harold Alberto Rodríguez Arias, Julio Cesar Rodríguez Ribón https://creativecommons.org/licenses/by-nc/4.0
State observer control for robotic series elastic actuators
This implementation shows the results through a control state observer strategy for a series elastic actuator (SEA) of motorized robotic limbs, with the purpose of evaluate the disturbance response with regard to convetional PID controller. By implementing a Matlab® script, the goal was to evaluate the state observer controller for a series elastic actuator space state dynamic model in comparison with a conventional PID controller, verifying the behavior of each by adding disturbances. The advantages of the state observer control strategy with respect to the conventional PID controller could be verified. The state observer ensures that the series elastic actuator is not affected by disturbances, presenting better performance than the PID in SEA control. The Matlab® simulation of the state space dynamic model of the series elastic actuator and its control by a state observer, shows the advantage that it offers in its dynamic response in scenarios with disturbances and eliminates its effect on the process in steady state.
Copyright (c) 2025 Frank Nixon Giraldo Ramos https://creativecommons.org/licenses/by-nc/4.0
Optimization model of the primary transport network in the food sector in Colombia
Logistics management is essential for organizations to generate competitive advantages, especially in Colombia, where geographic conditions and poor road infrastructure increase ground transportation costs. This study proposes a mixed-integer nonlinear programming model to optimize ground transportation costs in a food company, considering constraints such as regional warehouse demand, vehicle capacity, tray return, and use of outsourced transportation. The model's results show that optimal vehicle allocation not only reduces costs but also generates environmental benefits by reducing the number of necessary trips and prioritizing vehicles with a lower carbon footprint. Furthermore, the model ensures demand is met in terms of timeliness, quantity, and product conservation, contributing to the companies' competitiveness and reducing the environmental impact of their transportation operations.
Copyright (c) 2025 Hugo Fernando Castro Silva, Marling Carolina Cordero Díaz, Diego José Merchán Fernández https://creativecommons.org/licenses/by-nc/4.0
State of the art of quantum computing its challenges and applications
The article is a review of the state of the art of quantum computing, its challenges, and applications. The project methodology is based on a rigorous and structured approach that begins with the identification of relevant databases and information sources in the field of quantum computing. Then, inclusion and exclusion criteria are defined to select pertinent studies. The selected studies undergo critical analysis, and relevant data is extracted. The challenges of quantum computing are identified and discussed in the context of current advances in the field. Potential and current applications of quantum computing are explored in detail. Finally, the findings are synthesized and presented in a coherent and understandable manner. This approach allows for a deep and up-to-date understanding of the state of the art of quantum computing, its challenges, and applications.
Copyright (c) 2025 Richard Eliseo Mendoza Gáfaro, Edgar Alexis Albornoz Espinel, Heber Armando Pabón Conde https://creativecommons.org/licenses/by-nc/4.0
Step Up/Down Rectifier with Power Factor Correction based on a Cuk converter and sliding-mode control
The demand for reactive power from the distribution system and the production of current harmonics due to nonlinear active loads reduce the active power transport capacity, produce electrical losses and alter the voltage in the feeder buses of the distribution network. To face these challenges, this paper presents the design of a step-up/down rectifier and its control system to correct the power factor and mitigate the current harmonics produced by non-linear loads. The power interface is based on a Cuk converter, which enables to supply DC loads with voltages higher or lower than the peak value of the grid voltage. The Cuk converter is connected between the rectifier and the DC load. The main contribution of this work consists in a design method for the Cuk converter and its control system, ensuring specifications of the distribution system, the converter, and the load. The methodology consists of a design procedure of three controllers and the converter from their electrical and mathematical models. The design procedure is validated through two application examples simulated in the PSIM software. The results show the effectiveness of the design in mitigating harmonics, producing a power factor equal to one, maintaining low ripple and regulating the voltage at the load. The results show that the proposed design guarantees a ripple percentage in the grid of 2.5% and in the load of 5%, a power factor practically equal to unity, and voltage regulation in the expected number of cycles.
Copyright (c) 2025 Carlos Andrés Ramos Paja, Sergio Ignacio Serna Garcés, Andrés Julián Saavedra Montes https://creativecommons.org/licenses/by-nc/4.0
Optimization of energy consumption in a pisciculture system with Biofloc technology using a programmable logic controller (PLC)
Programmable logic controllers (PLC) are designed to monitor and regulate industrial processes. These electronic systems with programmable memory store control instructions, allowing specific functions to be executed based on the information received by the controllers. In fish farming, energy-intensive processes such as oxygenation and water recirculation are required. However, these processes can be automated using PLCs, adjusting the operating times and intensity of the equipment, allowing energy consumption to be reduced under optimal conditions for aquaculture production. The objective of the study was to implement a PLC-based automation system to monitor and control the Blowers in order to optimize energy consumption and improve the operational efficiency of the system. The methodology focused on the automation of the aeration of the fish farming system with biofloc technology. The results showed a significant reduction in energy consumption, leading to a decrease in production costs.
Copyright (c) 2025 Ingris Yohana Hernández Martínez, Pereira-Florez Luis Francisco , Escalante-Coronel Wilfer , Salazar-Sanchez Margarita del Rosario , José Fernando Solanilla Duque https://creativecommons.org/licenses/by-nc/4.0
Evaluation of the transtibial amputee gait using inertial sensors and cyclograms: impact of prosthetic misalignment
Gait in transtibial amputees involves significant biomechanical adaptations due to the absence of the distal segment of the lower limb, leading to alterations in movement patterns. Dynamic alignment of the prosthesis is essential for efficient locomotion but is often adjusted subjectively through clinical observation. This study analyzed the gait of three transtibial amputees using inertial sensors and cyclograms. The TECH-NAID® system, which employs inertial measurement units (IMUs), was used for motion capture, while cyclograms enabled a detailed and objective assessment of joint kinematics. Gait was evaluated under standard alignment and controlled misalignment conditions at the socket (abduction/adduction, flexion/extension) and the prosthetic foot (dorsiflexion/plantarflexion, inversion/eversion), with angular variations of 2°, 6°, and 10°. The results revealed significant alterations in the kinematics of the hip, knee, and ankle joints, as well as compensatory mechanisms between limbs. Cyclograms proved to be effective clinical tools for assessing gait deviations in prosthetic rehabilitation.
Copyright (c) 2025 Esperanza Camargo Casallas, Lely Adriana Luengas Contreras, Enrique Yamid Garzón González https://creativecommons.org/licenses/by-nc/4.0
A Multi-Modal ViT-Based Deep Learning Architecture for Binary Classification of Traffic Accident
Each year, more than 1 million people die due to traffic accidents, and one-third of these lives could be saved by reducing medical response time. Multi-Modal Deep Learning (MMDL) has emerged in recent years as a powerful tool that integrates different types of data to enhance decision-making capabilities in models. Additionally, Vision Transformers (ViT) are a Deep Learning approach for processing images and videos that has shown promising results in various fields of knowledge. In this project, we propose a ViT-based architecture for binary classification of traffic accidents using data from multiple sources, such as environmental data and images. The integration of an MMDL approach based on ViT can improve the model's accuracy in classifying accidents and non-accidents. This project explores a MMDL approach integrating ViT for traffic accident monitoring in the context of smart cities, achieving a recall of 91%, which evidences a high robustness of the model in identifying positive cases. However, the scarcity of multimodal data represents a major challenge for training these types of models.
Copyright (c) 2025 Jesús David Ríos Pérez, Germán Sánchez Torres, Carlos Henríquez Miranda https://creativecommons.org/licenses/by-nc/4.0
Visual Classification Algorithm for Chonto Tomatoes According to Standard NTC-1103-1 (Color, Size and Shape Parameters)
This article introduces the development and implementation a low-cost system for the classification of Chonto tomatoes according to their color, shape and size, in accordance with the Colombian technical standard NTC 1103-1. To achieve the proposed objective, a classification algorithm is developed using Python and OpenCV software. The obtained results show that the classification for color and maturity had an accuracy of 93%. In the classification by size the precision was 98%. Regarding the evaluation of eccentricity for determining the shape, an accuracy of 80% was obtained. The precision values mentioned above are comparisons with the results obtained manually by a trained individual, which are considered the ideal classification. However, the response time of the algorithm is 0.48 sec, in average, which is much less than the time required for human inspection and classification. In addition to precision achieved, it can be said that the developed software responds to the need to detect and classify chonto tomatoes according to their color, size and shape established in the Colombian technical standard NTC 1103- 1.
Copyright (c) 2025 Eduar Andrés Correa Cantillo, Leonel Felipe Sotelo Jiménez, Eugenio Yime Rodríguez, Javier Agustín Roldán Mckinley https://creativecommons.org/licenses/by-nc/4.0
Internet Access by Voice Commands: Navigation Application for Facebook, Gmail and Chrome
A system to navigate the internet using voice commands is presented. The implemented tool allowed verbal control of Google Chrome, Gmail and Facebook applications. The tests were conducted on a group of 33 people with different experiences browsing the Internet composed of young adults, older adults and people with motor disabilities. Each of the applications was tested separately using guided dialogues with voice commands and dictations. In the speech recognition system’s tests, 2871 voice commands and 594 dictations were used, observing a better result for voice commands in the Facebook application and dictation in the Google Chrome application. A general average of 84.69% with a standard deviation of 6.45% was obtained for the recognition of voice commands, and 74.63% with a standard deviation of 2.75% for the recognition of dictations
Information and Communications Technology
Copyright (c) 2025 José Hernando Mosquera Cruz, Humberto Loaiza Correa, Sandra Esperanza Nope Rodríguez https://creativecommons.org/licenses/by-nc/4.0
Strengthening critical educational infrastructures: a Red Team approach and advanced vulnerability assessment methodologies
This article delves into strengthening security in critical educational infrastructures using a Red Team approach for thorough vulnerability assessments. Applying methodologies like the Penetration Testing Execution Standard (PTES) and the Open Web Application Security Project (OWASP), the study identifies subtle vulnerabilities, emphasizing the need for a proactive approach. The Red Team perspective, mimicking attacker tactics, uncovers system weaknesses, allowing for preventive measures. The analysis highlights crucial concerns, particularly in Apache server configurations, stressing the need for continuous reviews and compatibility checks. Recommendations include adopting OWASP for preventive audits, regular server configuration updates, and strengthening firewalls for rapid anomaly response. Insights on Denial of Service attacks underscore the urgency of immediate action and a quick, effective response. The findings emphasize the importance of vigilant protection, paving the way for a resilient educational sector against evolving cyber threats.
Copyright (c) 2025 Isabel del Socorro Escobar Martínez, Katerine Marceles Villalba, Siler Amador Donado https://creativecommons.org/licenses/by-nc/4.0
Comparative technical study of topographic surveys in mountainous areas carried out with total station, GNSS equipment, and non-specialized UAV with and without control point support
This study compares three commonly used topographic technologies for mapping mountainous terrain: total station, GNSS equipment, and non-specialized UAV (with and without control points). The comparison considered chronological and technical criteria to determine the advantages and disadvantages of each technology. The study found that GNSS antennas, when they have optimal satellite reception and communication between the base and rover, offer the best performance compared to the other survey methods. They achieved accuracy similar to that of a total station, with considerably shorter execution times. Another finding was that the data collected with a UAV using control points allowed for a geomorphological description of the area but with significantly lower accuracy than the other technologies. These results emphasize the importance of performing a high densification of control points to achieve greater accuracy, even if it means increasing the required fieldwork time.
Copyright (c) 2025 Saieth Baudilio Chaves Pabón, Eder Felipe Muñoz Serna https://creativecommons.org/licenses/by-nc/4.0