Revistas UTB ( Universidad Tecnológica de Bolívar)
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Social innovation and digital transformation: education for older adults within the framework of Industry 4.0
Full text linkThe article proposes a social innovation strategy using university social service to promote the digital inclusion of older adults in the context of Industry 4.0. Grounded in a change management approach, it empowers university students as agents of transformation, implementing tailored educational programs. A five-phase framework (design, implementation, evaluation, conceptualization, and dissemination) offers a scalable solution to the digital divide, training students in intergenerational methodologies and using clear impact indicators such as skills gained and intergenerational perceptions. Implemented at the Faculty of Accounting and Administration at UABC, the program achieved notable results: 90% of older participants gained basic digital skills, and 98% of students reported improved perceptions of older generations, with many eager to replicate the initiative. The strategy highlights the role of inclusive approaches in digital transformation, demonstrating the value of intergenerational collaboration and providing a replicable model for other educational and institutional contexts
An adaptive energy monitoring system for a hybrid power plant using renewable energy
Full text linkClassical power plants powered by fossil fuels produce significant amounts of Greenhouse and toxic gases, together with additional environmentally harmful contaminants. Consequently, the greatest solution for the current issue is a power plant based on renewable resources. Researchers strongly advocate hybrid power plants (HPP) since environmental factors affect the affordability of renewable energy sources of a specific place as well as the time of availability. The present study emphasizes on developing an inventive model for a hybrid system using batteries, solar and wind energy that regulates the power generation as well as distribution according to the affordability of clean energy sources which satisfies load demand, charges or discharges the battery, and injects or utilizes grid power and/or electricity. The MALTAB/Simulink platform has been used to model and simulate the suggested hybrid power station and the EMS
Deep learning model for recognizing fresh and rotten fruits in industrial processes
Full text linkThe detection of fruit condition is essential to ensure quality control in industrial processes. Currently, this task is often performed manually, which is inefficient and time-consuming for operators. Therefore, it is crucial to implement emerging technologies that reduce human effort, costs, and production time while enabling more effective defect detection in fruits. In this context, this work presents the implementation of an artificial intelligence model based on computer vision to identify the condition of fruits. Various models were compared, including YOLOv8, YOLOv11, Detectron2, and Fast R-CNN, trained on a dataset that classifies fruits into two categories: ripe and rotten. The models were evaluated in terms of accuracy, speed, and robustness under different lighting and background conditions to select the most suitable for real-time applications. The results showed that YOLOv8 achieved the best generalization, reaching a mAP@50 of 83.8% and an accuracy of 77.3%
A case study of the energy performance of A-J hostel block in IIM, Bangalore
Full text linkHostel accommodations are vital to urban landscapes, serving diverse occupants like students and travelers. With rising energy demands and environmental concerns, enhancing the energy performance of hostels is increasingly essential. This research focuses on hostel buildings in Bangalore, India, a city known for its technological and educational excellence. Using advanced computational analysis and simulation tools such as Autodesk 2024 Revit and Insight, the study evaluates current energy consumption patterns and proposes optimization strategies. Detailed digital models of selected hostels are developed to examine factors influencing energy efficiency, including architectural design, insulation quality, and HVAC systems. The findings offer insights for hostel stakeholders in Bangalore and beyond, providing a framework for better energy efficiency and sustainability. Strategies encompass passive design principles and renewable energy integration. A case study of an IIM Bangalore hostel block demonstrates potential energy savings and cost reductions through these measures. The paper emphasizes that by adopting energy-efficient practices, hostels can significantly contribute to a greener urban environment
Enhancing cortical rhythms through robotic glove-assisted motor imagery training
Full text linkImproving Motor Imagery (MI) results in amplified event-related Desynchronization/Synchoronization (ERD/ERS), which is crucial for MI-based Brain-Computer Interface (BCIs) and neuromotor rehabilitation. Several attempts to enhance MI by providing visual guidance have been reported, however, this can be improved by using robotic systems for Kinesthetic MI (KMI), such as robotic gloves for hand movements. In this study, a novel protocol based on KMI tasks is proposed to analyze cortical rhythms against a standard MI protocol based on static Action Observation (AO). The results allow concluding that the use of the robotic gloves increases the ERDs by 3% during MI tasks, where neuromodulations were found to be more focused on the C3 and C4 electrodes during right- and left-hand closing MI, respectively, compared to opening. In conclusion, the proposed strategy based on passive movement is feasible and can enhance MI, which can be used for designing most robust BCIs
Design of controller for dual input non-isolated DC/DC converter
Full text linkRenewable energy sources such as solar, battery, ultra-capacitor, wind, and fuel cell are used for the generation of electrical energy. However, these energy sources will have distinct electrical characteristics. To incorporate these multiple energy sources into a drive system, a power modulator is required to transmit and receive the energy from source to load and load to source. In the conventional method, energy from various sources is achieved from several single-input converters, essentially a power converter. However, it has drawbacks like design complexity, huge cost, bulky nature, and reduced efficiency. As a result, the concept of Dual Input DC-DC Converters (DICs) evolved to capture the interest of energy integration experts. In this study, a dual-input non-isolated DC/DC converter with reduced switches and diode configuration was considered, and an attempt was made to develop a closed-loop control of the converter. Further, the performance of the converter is evaluated in MATLAB/SIMULINK by considering its electrical parameters and time-domain specifications. From the results, the converter provides an average output power of 2560 W, an efficiency of 96%, and a high output voltage of 670 V during boost mode of operation. Along with that, the closed-loop configuration provides a reduced rise time of 15 ms and 3.29 ms, peak time of 21.8 ms and 8.5 ms, settling time of 65.29 ms and 70.75 ms, and a steady-state error of zero in both PI-Boost and PI-Buck mode operations
To eggspace and beyond: design and implementation of an autogyro-CanSat with IoT purposes using AWS
Full text linkIn the context of a lack of educational tools for learning space technologies and satellite development, CanSats were created as an educational tool. This article proposes the mechanical, electrical and software design of a CanSat with an autogyro descent system where the novelty is the implementation of AWS IoT services and Node-RED to store, manipulate and display in real-time the collected weather data. This picosatellite design is capable of safeguarding the integrity of the CanSat's payload where a chicken egg will be placed during the flight and landing phases. Often, other designs of CanSats use local servers implemented on the computer or laptop of the team for storage and display of the data. This makes it more difficult to share the information to people without access to the computer where the server was specifically deployed. The use of AWS services for the Internet of Things is very useful in sharing and displaying the collected information to the public interested in the collected weather data. One of the AWS services implemented allows data subscription through Gmail. The findings made in this paper hold implications for applications involving the transportation and safe landing of delicate payloads in space exploration missions. As a result of the implementation of this design, the separation between the secondary and primary load was successfully achieved and the weather data was transmitted
Influence of window design and environmental variables on the window opening behavior of occupants and energy consumption in residential buildings
Full text linkBuilding energy use, thermal comfort, natural ventilation, and indoor air quality are influenced by the occupant behavior related to the opening and closing of windows in residential buildings. Studies about window opening and closing behaviour focused mainly on environmental variables (indoor temperature and air quality, climatic factors) and contextual parameters (season, time of the day). This paper investigates the influence of factors related to window design and environmental variables on the frequency of opening and closing the windows and the duration of windows in the open position. The impact of window opening behavior on residential energy consumption is also explored in this study. Data related to window characteristics, ease of operation, hours of windows in open/closed state, and frequency of opening and closing the windows are collected through a questionnaire survey from 365 residences. Energy consumption data is obtained from utility bills and weather data from the meteorological department. Among 365 residences, window opening and closing behaviour were monitored in three residences with loggers for a year to validate the data collected through the questionnaire survey. This study reiterated the influence of environmental variables on the windows’ open duration and the frequency of opening and closing the windows. The results reveal that the window characteristics influence the windows’ open duration and the frequency of opening and closing the windows. The study divulged that energy consumption is influenced by the hours the window is in an open state and the frequency of opening and closing the windows
Relationship between the human development index and the behavior of PM2.5 in USA, using multivariate statistics and machine learning
Full text linkThe scientific community has recently shown a rising interest in figuring out how atmospheric pollution affects the behavior of all-encompassing quality-of-life measures. The purpose is to show that bad air quality can have an impact on economic and educational factors in addition to people's health. This research seeks to establish the statistical association between the variables: population, demographic density, percentage of population at risk of poverty and the Human Development Index (HDI) of the United Nations, with the behavior of the average annual concentration of the pollutant PM2.5 in the USA. To achieve this multivariate regression models such as the generalized linear model and the logistic regression model were generated, in addition to generating a Bayesian classifier of neural networks to measure the predictive ability of the variables under study. As a result, the study was able to show that there is a connection between the Human Development Index, population size, and the proportion of the population at risk of poverty, as well as be-tween the average concentration of the pollutant PM2.5 and the likelihood that it will exceed the World Health Organization's upper limit. The major finding of the study is that poorer quality of life is related to higher levels of PM2.5 pollution concentration in the atmosphere. This is demonstrated by the pollutant's inverse link to both the percentage of the population at risk of poverty and the Human Development Index
Numerical and experimental investigations on a thermoelectric generator for electric power generation from waste heat recovery in a combined cycle power plant – an energy and economic (2E) analysis
Full text linkWith the ever-growing population in the world, the electricity demand has elevated drastically over the decades. Several kinds of research are being carried out to meet the electricity needs of the world with conventional and non-conventional energy sources. The conventional form of generating electricity from power plants has lesser efficiency and there is always scope for increasing the efficiency of power plants by using several heat recovery methods. The efficacy of the combined cycle power plant is around 62% where more amount of energy is dissipated as waste heat. The main objective of this study is to utilize the waste heat for power generation by effective utilization of Thermo-Electric Generators (TEGs). Therefore, the 32.5 MW combined cycle power plant located in Karaikal is chosen for this study. The powerplant uses HRSG to recover and utilize the waste heat to generate steam using it for the steam turbine. The study mainly focuses on the deployment of TEGs in the powerplant to generate electricity using waste heat. In this regard, the numerical analysis of TEGs under different conditions has been analysed and the best approach is chosen for experimental investigation. Further, an experimental prototype with similar operating conditions to a powerplant is developed and analyzed for the effect of TEGs in electric power generation. Finally, the cost-effectiveness of deploying TEGs in a power plant has been analysed using economic analysi