Examinando por Autor "Cabanillas-Carbonell, Michael"

Mostrando 1 - 20 de 37

Acceso abierto
“5G Technology in the Digital Transformation of Healthcare, a Systematic Review“
(MDPI, 2023-02-09) Cabanillas-Carbonell, Michael; Pérez-Martínez, Jorge; Yáñez, Jaime A.
“The world is currently facing one of the biggest problems related to health and the quality of healthcare. According to the goals outlined by WHO in the blueprint for sustainable development (SDG3), one of its objectives is to achieve universal health coverage and ensure a healthy lifestyle. In this regard, it is important to monitor and track the impact of applications that help address this problem. This systematic review provides an analysis of the impact of the 5G network on the use of apps to improve healthcare. An analysis of 343 articles was performed, obtaining 66 relevant articles, the articles were categorized into research conducted with fiber optic backbone network as well as future research. The main medical applications were identified as: telesurgery, mobile ultrasound, biosensor technology, robotic surgery and connected ambulance. In addition, it is classified and answer questions such as the most used to improve medical care and health quality, 5G-based applications used in media to improve medical care and health quality, databases and programming languages in telemedicine are the most used in 5G-based applications, the functionality available for telemedicine based on the use of 5G-based applications.“
Acceso abierto
“5G Technology in the Digital Transformation of Healthcare, a Systematic Review“
(MDPI, 2023-02-09) Cabanillas-Carbonell, Michael; Pérez-Martínez, Jorge; Yáñez, Jaime A.
“The world is currently facing one of the biggest problems related to health and the quality of healthcare. According to the goals outlined by WHO in the blueprint for sustainable development (SDG3), one of its objectives is to achieve universal health coverage and ensure a healthy lifestyle. In this regard, it is important to monitor and track the impact of applications that help address this problem. This systematic review provides an analysis of the impact of the 5G network on the use of apps to improve healthcare. An analysis of 343 articles was performed, obtaining 66 relevant articles, the articles were categorized into research conducted with fiber optic backbone network as well as future research. The main medical applications were identified as: telesurgery, mobile ultrasound, biosensor technology, robotic surgery and connected ambulance. In addition, it is classified and answer questions such as the most used to improve medical care and health quality, 5G-based applications used in media to improve medical care and health quality, databases and programming languages in telemedicine are the most used in 5G-based applications, the functionality available for telemedicine based on the use of 5G-based applications.“
Acceso abierto
Analysis of the Impact of the Pandemic on the Growth, Use, and Development of E-Business: A Systematic Review of the Literature
(MDPI, 2023-04-18) Ambrosio-Pérez, Milagros; Cabanillas-Carbonell, Michael; Iparraguirre-Villanueva, Orlando
The COVID-19 pandemic has affected various sectors in multiple countries, among them the economic sector has been one of the most affected, so the search for tools or measures for the continuation of sales and processes became recurrent, finding in e-business and its components precise tools to counteract the situation. Therefore, the present research aims to analyze the impact of the COVID-19 pandemic on the use, growth, and development of e-business by conducting a systematic literature review using the PRISMA methodology, collecting scientific articles covering the period of the pandemic from databases such as IEEE Xplore, ScienceDirect, Scopus, EBSCO, and IOPScience. Despite the limitations in access to scientific articles, it could be concluded that within the main characteristics identified, e-business tools in general allowed many businesses to continue subsisting and making sales thanks to the increase in online users due to the COVID-19 lockdowns. Although it was identified that the adoption of these tools lacked policies, limitations, and supports from governments, the perception of their use was positive in that they were considered safe and efficient.
Acceso abierto
Analysis of the Impact of the Pandemic on the Growth, Use, and Development of E-Business: A Systematic Review of the Literature
(MDPI, 2023-04-18) Ambrosio-Pérez, Milagros; Cabanillas-Carbonell, Michael; Iparraguirre-Villanueva, Orlando
The COVID-19 pandemic has affected various sectors in multiple countries, among them the economic sector has been one of the most affected, so the search for tools or measures for the continuation of sales and processes became recurrent, finding in e-business and its components precise tools to counteract the situation. Therefore, the present research aims to analyze the impact of the COVID-19 pandemic on the use, growth, and development of e-business by conducting a systematic literature review using the PRISMA methodology, collecting scientific articles covering the period of the pandemic from databases such as IEEE Xplore, ScienceDirect, Scopus, EBSCO, and IOPScience. Despite the limitations in access to scientific articles, it could be concluded that within the main characteristics identified, e-business tools in general allowed many businesses to continue subsisting and making sales thanks to the increase in online users due to the COVID-19 lockdowns. Although it was identified that the adoption of these tools lacked policies, limitations, and supports from governments, the perception of their use was positive in that they were considered safe and efficient.
Acceso abierto
Application of Learning Software in Basic Education Students with Intellectual Disabilities: A Systematic Review of the Literature
(International Association of Online Engineering, 2023-02-16) Vasquez Ubaldo, Alfredo; Gutierrez-Barreto, Vanessa; Sierra-Liñan, Fernando; Cabanillas-Carbonell, Michael
The world is currently facing the problem of the lack of education in basic education for students with intellectual disabilities. Therefore, it is important to follow up and monitor the various learning software that helps to address this problem. The study carried out is a review of scientific literature, which gathers research and studies, through a search in several databases: Dialnet, EBSCO, ERIC, IEEE Xplore, Redalyc, SAGE, ScienceDirect, Scopus, and Wiley. Likewise, according to certain previously defined inclusion and exclusion criteria, a total of two hundred (200) scientific articles were systematized, showing the digital technologies that facilitate the control, follow-up, and monitoring of the education of these students.
Acceso abierto
Application of Learning Software in Basic Education Students with Intellectual Disabilities: A Systematic Review of the Literature
(International Association of Online Engineering, 2023-02-16) Vasquez Ubaldo, Alfredo; Gutierrez-Barreto, Vanessa; Sierra-Liñan, Fernando; Cabanillas-Carbonell, Michael
The world is currently facing the problem of the lack of education in basic education for students with intellectual disabilities. Therefore, it is important to follow up and monitor the various learning software that helps to address this problem. The study carried out is a review of scientific literature, which gathers research and studies, through a search in several databases: Dialnet, EBSCO, ERIC, IEEE Xplore, Redalyc, SAGE, ScienceDirect, Scopus, and Wiley. Likewise, according to certain previously defined inclusion and exclusion criteria, a total of two hundred (200) scientific articles were systematized, showing the digital technologies that facilitate the control, follow-up, and monitoring of the education of these students.
Acceso abierto
Augmented reality for innovation: Education and analysis of the glacial retreat of the Peruvian Andean snow-capped mountains
(Elsevier B.V., 2023-09) Zapata-Paulini, Joselyn; Cabanillas-Carbonell, Michael; Iparraguirre-Villanueva, Orlando; Sierra-Liñan, Fernando; Baltozar-Clemente, Saul; Alvarez-Risco, Aldo; Yáñez, Jaime A.
Mountain glaciers are considered great reservoirs of water, and their importance lies in the fact that many of our ecosystems and numerous communities depend on them; Peru has one of the largest extensions of Andean snow-capped mountains, which have been affected by the decline in their glacier coverage and that is warned, will disappear due to environmental conditions and alterations in the current global temperature. This problem has increased due to ignorance, misinformation, indifference, and lack of solidarity on the part of the population who favors this discouraging situation. Taking advantage of the current technological immersion, in which we live, the development of a mobile application was proposed as a pedagogical resource to raise awareness among educational institutions about the glacial retreat of the Peruvian Andean snow-capped mountains, showing the current situation of some of the snow-capped mountains of the Andes that have suffered a greater impact, implementing augmented reality technology to obtain an interactive link. To provide greater detail of the situation, previous studies were carried out on glacial retreats in two Peruvian snow-capped mountains over the last 40 years, where it was found that, of the snow-capped mountains considered, Chicon had a decrease of 32.5% of its glacier cover, and Pumahuanca had a decrease of 56.9%. Such results are exposed within the application to provide realistic data on the glacial conditions of both Peruvian snow-capped mountains, as well as the consequences and conservation techniques to mitigate and cope with deglaciation. Taking into consideration that environmental education from an early age turns out to be key to forming an informed and participatory society about climate change.
Acceso abierto
“Comparison of Predictive Machine Learning Models to Predict the Level of Adaptability of Students in Online Education“
(Science and Information Organization, 2023) Iparraguirre-Villanueva, Orlando; Torres-Ceclén, Carmen; Epifanía-Huerta, Andrés; Castro-Leon, Gloria; Melgarejo-Graciano, Melquiades; Zapata-Paulini, Joselyn; Cabanillas-Carbonell, Michael
“With the onset of the COVID-19 pandemic, online education has become one of the most important options available to students around the world. Although online education has been widely accepted in recent years, the sudden shift from face-to-face education has resulted in several obstacles for students. This paper, aims to predict the level of adaptability that students have towards online education by using predictive machine learning (ML) models such as Random Forest (RF), KNearest-Neighbor (KNN), Support vector machine (SVM), Logistic Regression (LR) and XGBClassifier (XGB).The dataset used in this paper was obtained from Kaggle, which is composed of a population of 1205 high school to college students. Various stages in data analysis have been performed, including data understanding and cleaning, exploratory analysis, training, testing, and validation. Multiple parameters, such as accuracy, specificity, sensitivity, F1 count and precision, have been used to evaluate the performance of each model. The results have shown that all five models can provide optimal results in terms of prediction. For example, the RF and XGB models presented the best performance with an accuracy rate of 92%, outperforming the other models. In consequence, it is suggested to use these two models RF and XGB for prediction of students' adaptability level in online education due to their higher prediction efficiency. Also, KNN, SVM and LR models, achieved a performance of 85%, 76%, 67%, respectively. In conclusion, the results show that the RF and XGB models have a clear advantage in achieving higher prediction accuracy. These results are in line with other similar works that used ML techniques to predict adaptability levels. “
Acceso abierto
“Comparison of Predictive Machine Learning Models to Predict the Level of Adaptability of Students in Online Education“
(Science and Information Organization, 2023) Iparraguirre-Villanueva, Orlando; Torres-Ceclén, Carmen; Epifanía-Huerta, Andrés; Castro-Leon, Gloria; Melgarejo-Graciano, Melquiades; Zapata-Paulini, Joselyn; Cabanillas-Carbonell, Michael
“With the onset of the COVID-19 pandemic, online education has become one of the most important options available to students around the world. Although online education has been widely accepted in recent years, the sudden shift from face-to-face education has resulted in several obstacles for students. This paper, aims to predict the level of adaptability that students have towards online education by using predictive machine learning (ML) models such as Random Forest (RF), KNearest-Neighbor (KNN), Support vector machine (SVM), Logistic Regression (LR) and XGBClassifier (XGB).The dataset used in this paper was obtained from Kaggle, which is composed of a population of 1205 high school to college students. Various stages in data analysis have been performed, including data understanding and cleaning, exploratory analysis, training, testing, and validation. Multiple parameters, such as accuracy, specificity, sensitivity, F1 count and precision, have been used to evaluate the performance of each model. The results have shown that all five models can provide optimal results in terms of prediction. For example, the RF and XGB models presented the best performance with an accuracy rate of 92%, outperforming the other models. In consequence, it is suggested to use these two models RF and XGB for prediction of students' adaptability level in online education due to their higher prediction efficiency. Also, KNN, SVM and LR models, achieved a performance of 85%, 76%, 67%, respectively. In conclusion, the results show that the RF and XGB models have a clear advantage in achieving higher prediction accuracy. These results are in line with other similar works that used ML techniques to predict adaptability levels. “
Acceso abierto
Convolutional Neural Networks with Transfer Learning for Pneumonia Detection
(Science and Information Organization, 2022) Iparraguirre-Villanueva, Orlando; Guevara-Ponce, Victor; Roque Paredes, Ofelia; Sierra-Liñan, Fernando; Zapata-Paulini, Joselyn; Cabanillas-Carbonell, Michael
“Pneumonia is a type of acute respiratory infection caused by microbes, and viruses that affect the lungs. Pneumonia is the leading cause of infant mortality in the world, accounting for 81% of deaths in children under five years of age. There are approximately 1.2 million cases of pneumonia in children under five years of age and 180 000 died in 2016. Early detection of pneumonia can help reduce mortality rates. Therefore, this paper presents four convolutional neural network (CNN) models to detect pneumonia from chest X-ray images. CNNs were trained to classify X-ray images into two types: normal and pneumonia, using several convolutional layers. The four models used in this work are pre-trained: VGG16, VGG19, ResNet50, and InceptionV3. The measures that were used for the evaluation of the results are Accuracy, recall, and F1-Score. The models were trained and validated with the dataset. The results showed that the Inceptionv3 model achieved the best performance with 72.9% accuracy, recall 93.7%, and F1-Score 82%. This indicates that CNN models are suitable for detecting pneumonia with high accuracy.“
Acceso abierto
Convolutional Neural Networks with Transfer Learning for Pneumonia Detection
(Science and Information Organization, 2022) Iparraguirre-Villanueva, Orlando; Guevara-Ponce, Victor; Roque Paredes, Ofelia; Sierra-Liñan, Fernando; Zapata-Paulini, Joselyn; Cabanillas-Carbonell, Michael
“Pneumonia is a type of acute respiratory infection caused by microbes, and viruses that affect the lungs. Pneumonia is the leading cause of infant mortality in the world, accounting for 81% of deaths in children under five years of age. There are approximately 1.2 million cases of pneumonia in children under five years of age and 180 000 died in 2016. Early detection of pneumonia can help reduce mortality rates. Therefore, this paper presents four convolutional neural network (CNN) models to detect pneumonia from chest X-ray images. CNNs were trained to classify X-ray images into two types: normal and pneumonia, using several convolutional layers. The four models used in this work are pre-trained: VGG16, VGG19, ResNet50, and InceptionV3. The measures that were used for the evaluation of the results are Accuracy, recall, and F1-Score. The models were trained and validated with the dataset. The results showed that the Inceptionv3 model achieved the best performance with 72.9% accuracy, recall 93.7%, and F1-Score 82%. This indicates that CNN models are suitable for detecting pneumonia with high accuracy.“
Acceso abierto
Design of a Mobile Application for the Logistics Process of a Fire Company
(Science and Information Organization, 2022) Parra Aquije, Luis Enrique; Vasquez Carranza, Luis Gustavo; Alfaro Pena, Gustavo Bernnet; Cabanillas-Carbonell, Michael; Andrade-Arenas, Laberiano
“Currently, the logistics process is an important part for any company because it helps to manage the assets and products that enter and leave it. Some companies carry out this process physically, saving the information on sheets of paper or Excel files, which takes longer to do and is not at the forefront of how companies do it, which is by using mobile applications to improve this process. Likewise, it has been decided to implement a mobile application with the aim of improving the logistics process in the Callao No. 15 fire company. For the elaboration of the application, the RUP methodology was used to do it in a more optimal way, in the end, a survey of experts in Google Forms was conducted, addressed to 10 experts to know the evaluation of the mobile application. In the end, a favorable result was obtained from the opinion of the experts on the mobile application; 70% of the respondents indicate that the usability of the mobile application has a “Very high” level;it can be seen that 80% of respondents indicate that the presentation of the mobile the application has a “Very high” level; it can be seen that 90% of the respondents indicate that the functionality of the mobile application has a “Very high” level; besides,it can be seen that 80% of the respondents indicate that the security of the mobile application has a “Very high” level.“
Acceso abierto
“Design of a Mobile Application for the Logistics Process of a Fire Company“
(Science and Information Organization, 2022) Parra Aquije, Luis Enrique; Vasquez Carranza, Luis Gustavo; Alfaro Pena, Gustavo Bernnet; Cabanillas-Carbonell, Michael; Andrade-Arenas, Laberiano
“Currently, the logistics process is an important part for any company because it helps to manage the assets and products that enter and leave it. Some companies carry out this process physically, saving the information on sheets of paper or Excel files, which takes longer to do and is not at the forefront of how companies do it, which is by using mobile applications to improve this process. Likewise, it has been decided to implement a mobile application with the aim of improving the logistics process in the Callao No. 15 fire company. For the elaboration of the application, the RUP methodology was used to do it in a more optimal way, in the end, a survey of experts in Google Forms was conducted, addressed to 10 experts to know the evaluation of the mobile application. In the end, a favorable result was obtained from the opinion of the experts on the mobile application; 70% of the respondents indicate that the usability of the mobile application has a “Very high” level;it can be seen that 80% of respondents indicate that the presentation of the mobile the application has a “Very high” level; it can be seen that 90% of the respondents indicate that the functionality of the mobile application has a “Very high” level; besides,it can be seen that 80% of the respondents indicate that the security of the mobile application has a “Very high” level.“
Acceso abierto
Development and evaluation of a didactic tool with augmented reality for Quechua language learning in preschoolers
(Institute of Advanced Engineering and Science, 2023-01-09) Zapata-Paulini, Joselyn; Beltozar-Clemente, Saul; Sierra-Liñan, Fernando; Cabanillas-Carbonell, Michael
“It is important to preserve our cultural identity through the preservation of our mother tongue, contributing to its dissemination. Augmented reality (AR) is a great ally of education that provides efficiency, and productivity and increases the interest of students in their academic activities. An AR application was developed for learning Quechua in preschool children, thus improving their learning, satisfaction, and preference compared to traditional teaching. Previously, learning styles were identified for better coverage of the application; the design thinking methodology was applied for the development of the application, then the respective tests were conducted where it was obtained that the children's performance improved by 28.3% more compared to traditional teaching, with an average satisfaction of 89% of the classrooms, and 81% of students' preference. It was concluded that the proposed application considerably favors the written and audiovisual learning of the Quechua language in preschool students. “
Acceso abierto
“Digital Tool for Film Promotion Through the Use of Augmented Reality“
(International Association of Online Engineering, 2023-01) Beltozar-Clemente, Saul; Sierra-Liñan, Fernando; Pucuhuayla-Revatta, Félix; Zapata-Paulin, Joselyn; Cabanillas-Carbonell, Michael
“After the isolation caused by the pandemic, the entertainment sector has been forced to change the way it markets its products and services, and users have been adapting to the change. The objective of this research article is to provide added value and innovation to the advertising promotions of movies in the premiere, through the development of a mobile application based on augmented reality to improve customers’ shopping experience. For which the Agile Mobile-D Methodology was used for the development of the application and the results were studied using 5 indicators: Time to choose a movie, where an improvement of 38.26% was obtained compared to the Pre-Test; regarding the indicator time to acquire information about the movie, an improvement of 81.33% was obtained. 33%; concerning the third indicator, time to initiate the purchase, an improvement of 88% was obtained; concerning the fourth indicator, time to obtain a reminder, an improvement of 83.33% was obtained, making the time with the use of the application shorter; finally, concerning the customer satisfaction indicator, 73% of the users who used the application rated their experience as between satisfied and very satisfied.“
Acceso abierto
Disease Identification in Crop Plants based on Convolutional Neural Networks
(Science and Information Organization, 2023) Iparraguirre-Villanueva, Orlando; Guevara-Ponce, Victor; Torres-Ceclén, Carmen; Ruiz-Alvarado, John; Castro-Leon, Gloria; Roque-Paredes, Ofelia; Zapata-Paulini, Joselyn; Cabanillas-Carbonell, Michael
“The identification, classification and treatment of crop plant diseases are essential for agricultural production. Some of the most common diseases include root rot, powdery mildew, mosaic, leaf spot and fruit rot. Machine learning (ML) technology and convolutional neural networks (CNN) have proven to be very useful in this field. This work aims to identify and classify diseases in crop plants, from the data set obtained from Plant Village, with images of diseased plant leaves and their corresponding Tags, using CNN with transfer learning. For processing, the dataset composing of more than 87 thousand images, divided into 38 classes and 26 disease types, was used. Three CNN models (DenseNet-201, ResNet-50 and Inception-v3) were used to identify and classify the images. The results showed that the DenseNet-201 and Inception-v3 models achieved an accuracy of 98% in plant disease identification and classification, slightly higher than the ResNet-50 model, which achieved an accuracy of 97%, thus demonstrating an effective and promising approach, being able to learn relevant features from the images and classify them accurately. Overall, ML in conjunction with CNNs proved to be an effective tool for identifying and classifying diseases in crop plants. The CNN models used in this work are a very good choice for this type of tasks, since they proved to have a very high performance in classification tasks. In terms of accuracy, all three models are very accurate in image classification, with an accuracy of over 96% with large data sets“
Acceso abierto
Disease Identification in Crop Plants based on Convolutional Neural Networks
(Science and Information Organization, 2023) Iparraguirre-Villanueva, Orlando; Guevara-Ponce, Victor; Torres-Ceclén, Carmen; Ruiz-Alvarado, John; Castro-Leon, Gloria; Roque-Paredes, Ofelia; Zapata-Paulini, Joselyn; Cabanillas-Carbonell, Michael
“The identification, classification and treatment of crop plant diseases are essential for agricultural production. Some of the most common diseases include root rot, powdery mildew, mosaic, leaf spot and fruit rot. Machine learning (ML) technology and convolutional neural networks (CNN) have proven to be very useful in this field. This work aims to identify and classify diseases in crop plants, from the data set obtained from Plant Village, with images of diseased plant leaves and their corresponding Tags, using CNN with transfer learning. For processing, the dataset composing of more than 87 thousand images, divided into 38 classes and 26 disease types, was used. Three CNN models (DenseNet-201, ResNet-50 and Inception-v3) were used to identify and classify the images. The results showed that the DenseNet-201 and Inception-v3 models achieved an accuracy of 98% in plant disease identification and classification, slightly higher than the ResNet-50 model, which achieved an accuracy of 97%, thus demonstrating an effective and promising approach, being able to learn relevant features from the images and classify them accurately. Overall, ML in conjunction with CNNs proved to be an effective tool for identifying and classifying diseases in crop plants. The CNN models used in this work are a very good choice for this type of tasks, since they proved to have a very high performance in classification tasks. In terms of accuracy, all three models are very accurate in image classification, with an accuracy of over 96% with large data sets“
Acceso abierto
Enterprise information security risks: a systematic review of the literature
(Institute of Advanced Engineering and Science, 2023-05-06) Lavalle Sandoval, Jenner; Andrade-Arenas, Laberiano; Hernández Celis, Domingo; Cabanillas-Carbonell, Michael
Currently, computer security or cybersecurity is a relevant aspect in the area of networks and communications of a company, therefore, it is important to know the risks and computer security policies that allow a unified management of cyber threats that only seek to affect the reputation or profit from the confidential information of organizations in the business sector. The objective of the research is to conduct a systematic review of the literature through articles published in databases such as Scopus and Dimension. Thus, in order to perform a complete documentary analysis, inclusion and exclusion criteria were applied to evaluate the quality of each article. Then, using a quantitative scale, articles were filtered according to author, period and country of publication, leaving a total of 86 articles from both databases. The methodology used was the one proposed by Kitchenham, and the conclusion reached was that the vast majority of companies do not make a major investment in the purchase of equipment and improvement of information technology (IT) infrastructure, exposing themselves to cyber-attacks that continue to grow every day. This research provides an opportunity for researchers, companies and entrepreneurs to consult so that they can protect their organization's most important assets.
Acceso abierto
Free Hardware based System for Air Quality and CO2 Monitoring
(Science and Information Organization, 2022) Alvarez-Mendoza, Cristhoper; Vilchez-Lucana, Jhon; Sierra-Liñan, Fernando; Cabanillas-Carbonell, Michael
“Due to the increase in air pollution, especially in Latin American countries of low and middle income, great environmental and health risks have been generated, highlighting that there is more pollution in closed environments. Given this problem, it has been proposed to develop a system based on free hardware for monitoring air quality and CO2, in order to reduce the levels of air pollution in a closed environment, improving the quality of life of people and contributing to the awareness of the damage caused to the environment by the hand of man himself. The system is based on V-Model, complemented with a ventilation prototype implemented with sensors and an application for its respective monitoring. The sample collected in the present investigation was non-probabilistic, derived from the reports of air indicators during 15 days with specific schedules of 9am, 1pm and 6pm. The results obtained indicated that the air quality decreased to 670 ppm, as well as the collection time decreased to 5 seconds and finally the presence of CO2 was reduced to 650 ppm after the implementation of the system, achieving to be within the standards recommended by the World Health Organization. “
Acceso abierto
Free Hardware based System for Air Quality and CO2 Monitoring
(Science and Information Organization, 2022) Alvarez-Mendoza, Cristhoper; Vilchez-Lucana, Jhon; Sierra-Liñan, Fernando; Cabanillas-Carbonell, Michael
Due to the increase in air pollution, especially in Latin American countries of low and middle income, great environmental and health risks have been generated, highlighting that there is more pollution in closed environments. Given this problem, it has been proposed to develop a system based on free hardware for monitoring air quality and CO2, in order to reduce the levels of air pollution in a closed environment, improving the quality of life of people and contributing to the awareness of the damage caused to the environment by the hand of man himself. The system is based on V-Model, complemented with a ventilation prototype implemented with sensors and an application for its respective monitoring. The sample collected in the present investigation was non-probabilistic, derived from the reports of air indicators during 15 days with specific schedules of 9am, 1pm and 6pm. The results obtained indicated that the air quality decreased to 670 ppm, as well as the collection time decreased to 5 seconds and finally the presence of CO2 was reduced to 650 ppm after the implementation of the system, achieving to be within the standards recommended by the World Health Organization.