Recent Submissions

  • Cybersecurity maturity model for the protection and privacy of personal health data

    Rojas, Aaron Joseph Serrano; Valencia, Erick Fabrizzio Paniura; Armas-Aguirre, Jimmy; Molina, Juan Manuel Madrid (Institute of Electrical and Electronics Engineers Inc., 2022-01-01)
    This paper proposes a cybersecurity maturity model to assess the capabilities of medical organizations to identify their level of maturity, prioritizing privacy and personal data protection. There are problems such as data breaches, the lack of security measures in health information, and the poor capacity of organizations to handle cybersecurity threats that generate concern in the health sector as they seek to mitigate risks in cyberspace. The proposal, based upon C2M2 (Cybersecurity Capability Maturity Model), incorporates practices and controls which allow organizations to identify security gaps generated through cyberattacks on sensitive health patient data. This model seeks to integrate the best practices related to privacy and protection of personal data in the Peruvian legal framework through the Administrative Directive No. 294-MINSA and the personal data protection Act No. 29733. The model consists of 3 evaluation phases. 1. Assessment planning; 2. Execution of the evaluation; 3. Implementation of improvements. The model was validated and tested in a public sector medical organization in Lima, Peru. The preliminary results showed that the organization is at Level 1 with 14% of compliance with established controls, 34% in risk, threat and vulnerability management practices and 19% in supply chain management. These the 3 highest percentages of the 10 evaluated domains.
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  • Traffic accident monitoring system using radio frequency identification tools

    Pardo, Eduardo Martin Estela; Chero, Jhonatan Axel Yataco; Aguirre, Jimmy Armas; Acosta, Alvaro Chavarri (Institute of Electrical and Electronics Engineers Inc., 2022-01-01)
    This article proposes a system that allows monitoring car accidents with the use of NFC technology. The solution is comprised of low-cost Radio Frequency Identification (RFID) tools integrated into a mobile and web application that interact with the Google Maps API for efficient monitoring. The car accident reporting process collects and sends data manually through different service channels, which generates delays and, in some cases, the receipt of erroneous data. The proposed solution automates the accident reporting process by storing data from the users involved in the RFID tags and displaying them in the mobile and web applications, when generating a new report. Also, our application interacts with the Google Maps API to show the exact location from where accidents are reported, in order to speed up the process of attention by the PNP. The validation was carried out in the city of Lima, Peru. Preliminary results yielded data showing a 94% reduction in the accident reporting process and a 94% reduction in the average data capture time by the National Police of Peru (PNP).
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  • Technological Model Based on Blockchain Technology for Genetic Information Protection in the Health Sector

    Arroyo-Mariños, Julio; Mejia-Valle, Karla; Ugarte, Willy (Springer Science and Business Media Deutschland GmbH, 2023-01-01)
    In the health industry, the transparency of product data registration in the supply chain is a critical aspect in determining the source of genetic data. Various upcoming technologies, such as blockchain, can help with this challenge. Blockchain is a shared and immutable database that makes recording transactions and tracking assets in a commercial network easier. Currently, genetic information is regarded as a vital asset in the health sector, as more precise diagnostic samples in medical genomics enable improved treatments for patients suffering from a variety of disorders. Since actions connected to the storage or management of data might have several areas of vulnerability, this paper describes the development of a technological model employing Blockchain as technology to assure the protection of genetic information in the private health sector. Furthermore, unauthorized activities such as registration and access control in the exchange of genetic information have been carried out, primarily through entities that manage the eligibility of users with genomics information and grant access to specific data sets, demonstrating a lack of harmonization in access policies between the owners of genetic information and the health entities that manage it. A proof-of-concept was carried out to evaluate the model’s capabilities and ensure that a larger-scale deployment could be carried out. Experts agreed with our proposal, and consumers would be prepared to employ proof of concept to assure traceability and security of their data, according to the evaluation.
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  • A Technological Solution to Supervise CoViD-19 Symptoms in Senior Patients in Lima

    Haro-Hoyo, Sara; Inga-Quillas, Edgard; Ugarte, Willy (Springer Science and Business Media Deutschland GmbH, 2023-01-01)
    The article’s objective is to outline the application of a technological solution based on wearable technology that provides for the best possible monitoring of elderly patients with CoViD19. This is a pressing issue right now because the epidemic has caused numerous problems for senior patients. For example, because older persons are more susceptible to CoViD19, they must limit social contact or adhere to stricter lockdown protocols. In order to do this, a thorough assessment of the relevant scientific literature in the phases of planning, development, and analysis was conducted. The use of technology models in real time, the monitoring of CoViD19 symptoms, and the usage of IoT for geriatric patient monitoring are all topics covered in this paper. Our findings demonstrate the viability of our strategy.
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  • Evaluating the Depression Level Based on Facial Image Analyzing and Patient Voice

    Ramos-Cuadros, Alexander; Santillan, Luis Palomino; Ugarte, Willy (Springer Science and Business Media Deutschland GmbH, 2023-01-01)
    Depression is regarded as a widespread mental condition that affects people of all ages. It has a negative impact on a variety of aspects of life, including mood, vigor, and interests in enjoying activities. In the most severe cases, depression can also result in suicide. creating the chance for collaboration between mental health professionals and the use of technical tools to enhance the assessment of the severity of depression to offer the patient with an ideal clinical diagnosis and an appropriate referral to begin treatment. The COVID-19 epidemic in Peru has decreased face-to-face interaction and quick access to medical professionals, making it more difficult for patients’ mental health to be identified or treated effectively, which results in the disease becoming chronic, psychological suffering, and high costs associated with specialized care. The implementation of a technology model that assesses degrees of recurrent depression by examining facial photos and voice to identify the chronicity of depressive symptoms in young Peruvians is thus one of the research’s problems. Our findings demonstrate that, based on the functions of the mobile application, adolescent patients were predisposed to complete a self-administered depression questionnaire in a simulated setting with an optimal feeling of satisfaction and usefulness.
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  • Cybersecurity framework for SMEs in Peru based on ISO/IEC 27001 and CSF NIST controls

    Angelo Edu, Munoz Luyo; Alexis, Garibay Palomino; Lenis, Wong Portillo (IEEE Computer Society, 2023-01-01)
    Due to the global pandemic that was experienced in 2020, the Small and Medium Enterprises (SMEs) sector in Peru chose to store all their information in cloud services. However, a 2021 Kaspersky study indicates that SMBs have few resources to implement security solutions to protect their information. For this reason, this article proposes a cybersecurity framework composed of controls from ISO/IEC 27001 and the Cybersecurity Framework (CSF) of the National Institute of Standards and Technology (NIST) to mitigate cyber-threats against SMEs in Peru. The framework consists of 7 steps having as reference the Deming cycle (PDCA). For the implementation of the composite framework, we worked with 12 domains and 40 controls for a Peruvian SME in the technology sector. The results showed an increase in cybersecurity of 40 %, after applying the 40 controls, improving its level of maturity from the 'insufficient' state to a 'mature' state, according to the assessment given.
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  • A Process Discovery and Conformance Checking Integration System for the Optimization of Resources in the Application of Process Mining

    Marin, Enrique Martin Saqui; Rivera, Victor Manuel Yamunaque; Armas-Aguirre, Jimmy; Aguirre, Santiago (IEEE Computer Society, 2023-01-01)
    In this paper, we present a novel system that combines process discovery and conformance checking to optimize resource usage in the operations area of banking companies. Our proposed system improves upon previous solutions by integrating real-time process mining techniques to reduce resource consumption in banking operations. The use of real-time process mining techniques in the proposed system enables faster error identification in processes, emphasizing the importance of such techniques for banking companies. The system is comprised of two integrated process mining techniques, as reported in existing literature. Process discovery involves two key components: dataset generation and process visualization. Additionally, compliance checking involves process monitoring, alerts, and reports. To validate the effectiveness of our system, we conducted a stress test, which was evaluated by experienced process mining users with extensive experience in the banking sector in Lima, Peru. Preliminary results of the stress test demonstrated a significant improvement in system performance, with a 37.42% increase in the capacity of web requests per minute and a total of 82.86% of requests successfully answered. These results enabled corrective and preventive actions to be taken, indicating the practical value of our proposed system in optimizing resource usage in banking operations. In conclusion, our system provides a robust solution to optimize resource usage in the operations area of banking companies and emphasizes the importance of real-time process mining techniques in achieving this goal. The system has been validated through a stress test and evaluation by experienced users in the banking sector, further indicating its practical applicability.
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  • A Learning Health-Care System for Improving Renal Health Services in Peru Using Data Analytics

    Mita, Vielka; Castillo, Liliana; Castillo-Sequera, José Luis; Wong, Lenis (International Association of Online Engineering, 2023-01-01)
    The health sector around the world faces the continuous challenge of improving the services provided to patients. Therefore, digital transformation in health services plays a key role in integrating new technologies such as artificial intelligence. However, the health system in Peru has not yet taken the big step towards digitising its services, currently ranking 71st according to the World Health Organisation (WHO). This article proposes a learning health system for the management and monitoring of private health services in Peru based on the three key components of intelligent health care: (1) a health data platform (HDP); (2) intelligent technologies (IT); and (3) an intelligent health care suite (HIS). The solution consists of four layers: (1) data source, (2) data warehousing, (3) data analytics, and (4) visualization. In layer 1, all data sources are selected to create a database. The proposed learning health system is built, and the data storage is executed through the extract, transform and load (ETL) process in layer 2. In layer 3, the Kaggle dataset and the decision tree (DT) and random forest (RF) algorithms are used to predict the diagnosis of disease, resulting in the RF algorithm having the best performance. Finally, in layer 4, the intelligent health-care suite dashboards and interfaces are designed. The proposed system was applied in a clinic focused on preventing chronic kidney disease. A total of 100 patients and six kidney health experts participated. The results proved that the diagnosis of chronic kidney disease by the learning health system had a low error rate in positive diagnoses (err = 1.12%). Additionally, it was demonstrated that experts were “satisfied” with the dashboards and interfaces of the intelligent health-care suite as well as the quality of the learning health system.
    Acceso abierto
  • Application prototype for the registration, checking, and monitoring of perishable foods

    Cutipa, Azana; Williams, Edwin; Arias, Cervera; Gianfranco; Tuesta, Quispe; Enrique, Julio (Institute of Electrical and Electronics Engineers Inc., 2023-01-01)
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  • Assessment System for Physical Abuse in adolescents caused by Domestic Violence

    Caytuiro, Yesenia Cruzado; Navarro Mantari, Kerling A.; Durango, Daniel Wilfredo Burga (Institute of Electrical and Electronics Engineers Inc., 2022-01-01)
    Research shows that around 300 million children in the world live in situations of violence in their homes. In addition, it is mentioned that the attention to these cases is not adequate in terms of attention time and treatment [1]. This paper presents a web application which obtains statistics in real time that allows specialists to show cases of physical abuse and thus be able to intervene quickly. We present a system based on Amazon Web Services (AWS) made with MySql database and the RDS service. Compared to the traditional method, a survey carried out on paper and with a data processing time. This comparison showed that the average data capture rate is lower than with the traditional method since the data is uploaded to the network instantly without the need to digitize the responses and it can also be used anywhere with internet access.
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  • Web Solution Based on QR Code for the Traceability of the Wood Transformation Process

    Amaya, Edgar Diaz; Rojas, Omar Troncos; Guerrero, Mario Paiva (Institute of Electrical and Electronics Engineers Inc., 2022-01-01)
    The information's management on the traceability of wood in Peru is complicated by multiple causes. In this article we present our project, which seeks to propose a technological model that allows greater efficiency in the management of timber information so that sawmills in Peru can improve their administration. Our proposed model allows us to appreciate a possible improvement in the time it takes to obtain information on the traceability of wood compared to the traditional way in which work continues in Peru. Also, in the investigation a prototype application of traceable information was developed. The main contribution of the research consists in the design of a technological model that serves as a reference to develop a technological solution for the traceability of wood in Peru.
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  • HydroTi: An Irrigation System for Urban Green Areas using IoT

    Carrillo-Pasiche, Piero; Miranda-Gutarra, Anthony; Ugarte, Willy (Institute of Electrical and Electronics Engineers Inc., 2022-01-01)
    Irrigation systems and their performance to efficiently accomplish their function have gained notoriety in recent years. Therefore, those systems are not capable of approaching many factors as water-saving and irrigation automation. Here we present a new irrigation system based on the IoT, analyzing the most important factors that involve an efficient irrigation process taking into consideration water usage and saving this resource. Thus, we developed a prototype using Arduino Uno which is connected to sensors that can lead a web application named HydroTi to determine when to irrigate and how much water to use. This function was enabled by Adafruit IO, a web service useful for IoT projects. To validate the effectiveness of this solution, we compared different irrigation types to determine that the automatic irrigation mode of HydroTi is better w.r.t. water consumption in Metropolitan Lima, Peru urban areas.
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  • Reference Model for the Development of a Learning Management System with an Integrated Voice Assistant for the Optimization of the Teaching Process of a Foreign Language for People with Visual Impairment

    Begazo, Mayber Javier Celis; Durango, Daniel Wilfredo Burga (Institute of Electrical and Electronics Engineers Inc., 2022-01-01)
    Visually impaired people experience different accessibility barriers when they want to learn a second language through virtual classes. In addition to this, Screen Readers often have a high learning curve, plus they are not optimized for reading different languages at the same time. For this reason, it was decided to design the model of a Learning Management System (LMS) with a minimalist and accessible design and with an integrated voice assistant. As a result, it was obtained that the proposed solution was more efficient and effective in providing support to the process of teaching foreign languages in contrast to the methodology currently used.
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  • System to evaluate the medical teleconsultation service in public health centers in Peru

    Guzman, Diego Arrospide; Verastegui, Melisa Camila Bravo; Durango, Daniel Wilfredo Burga (Institute of Electrical and Electronics Engineers Inc., 2022-01-01)
    The investigation of the existing information has shown that there is a high waiting time for the scheduling and especially the attention of medical appointments. This paper presents THANI, a medical teleconsultation system aimed at the public sector, which aims to reduce long waiting times for medical appointments through a web platform that integrates all the benefits of telehealth. This system allows waiting times to be reduced by improving and redesigning the traditional flow that takes place in public health centers in Peru, which have proven to be inefficient and generate user dissatisfaction. We apply satisfaction surveys to the main users of the system: patients. This evaluation showed a considerable improvement in terms of medical appointment times, improving the experience of patients and medical providers of health services by reducing the time of attending medical appointments from 80 minutes on average to 30 minutes, which implies a saving of approximately 50 minutes.
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  • Develop a Model for Assessing the Most Efficient Diseases Diagnosis using Machine Learning

    Vives, Luis; Basha, N. Khadar; Poonam; Gehlot, Anita; Chole, Vikrant; Pant, Kumud (Institute of Electrical and Electronics Engineers Inc., 2022-01-01)
    so, machine learning techniques are being developed to improve performance and maintenance prediction. Increasing our knowledge of the relationship between humans and algorithms, Because data is so valuable, improving strategies for intelligently having to manage the now-ubiquitous content infrastructures is a necessary part of the process toward completely autonomous agents. Numerous researchers recently developed numerous computer-aided diagnostic algorithms employing various supervised learning approaches. Early identification of sickness may help to reduce the number of people who die as a result of these illnesses. Using machine learning techniques, this research creates an efficient automated illness diagnostic algorithm. We chose three key disorders in this paper: coronavirus, cardiovascular diseases, and diabetes. The data are inputted into a mobile application in the suggested model, the investigation is then done in a real-time dataset that used a pre-trained model machine learning technique trained within the same dataset then implemented in firebase, and lastly, the illness identification result can be seen in the mobile application. Logistic regression is a method of prediction calculation
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  • A decision tree–based classifier to provide nutritional plans recommendations

    Aguilar-Loja, Omar; Dioses-Ojeda, Luis; Armas-Aguirre, Jimmy; Gonzalez, Paola A. (IEEE Computer Society, 2022-01-01)
    The use of machine learning algorithms in the field of nutritional health is a topic that has been developed in recent years for the early diagnosis of diseases or the recommendation of better nutritional habits. People with poor diets are more prone to chronic diseases and, in the long term, this can lead to dead. This study proposes a model for the recommendation of nutritional plans using the decision tree technique considering the patient data, in complement with the BMI (Body Mass Index) and BMR (Basal Metabolic Rate) to evaluate and recommend the best nutritional plan for the patient. The algorithm used in the model was trained with a dataset of meal plan data assigned by specialists which were obtained from the Peruvian food composition table, and the data from the diets that were assigned and collected from the nutrition area of the Hospital Marino Molina Sccipa in Lima, Peru. Preliminary results of the experiment with the proposed algorithm show an accuracy of 78.95% allowing to provide accurate recommendations from a considerable amount of historical data. In a matter of seconds, these results were obtained using Scikit learn library. Finally, the accuracy of the algorithm has been proven, generating the necessary knowledge so that it can be used to create appropriate nutritional plans for patients and to improve the process of creating plans for the nutritionist.
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  • Implementation of Lean Manufacturing Principles to increase Productivity in SMEs in the manufacturing sector of clothing

    Arica-Hernandez, Marco Antonio; Llagas-Llontop, Sebastian Eduardo; Khaburzaniya, Irakliy (Association for Computing Machinery, 2022-01-12)
    SMEs in the textile sector face many problems in their production flows, mainly due to the lack of production management systems caused by poor management of the production chain. Therefore, a diagnostic analysis is carried out in a textile SME to evaluate and define the deficiencies and factors that affect its competitiveness, which began with the analysis of the current situation of the company, where it was established the existence of poor-quality management, high waiting times and lack of procedures. Therefore, the use of lean manufacturing tools such as Jidoka, Single Minute Exchange of Die with respect to the production line and process management for the measurement and control of operations in the production area is proposed. The incorporation of these tools in block allows to decrease the rates of defective products, the excess of operative work and the set-up of the machines for the change of model. The main result of the research was that production increased to 0.091 und/PEN.
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  • Efficient Grocery Shopping Using Geolocation and Data Mining

    Aliaga-Vasquez, Myrella; Bramon-Ayllon, Reyna; Ugarte, Willy (IEEE Computer Society, 2022-01-01)
    In the current pandemic, people are looking to leave their houses less frequently to prevent getting infected, but the absence of an app that shows the necessary information before going to the supermarket forces people to look in different supermarkets for the products they want to buy, thus increasing their chances of catching the virus, not to mention the waste of money and time. DoremyS is an app that allows you to create shopping lists that indicate to the user which supermarket to visit to find every product in them; it uses Geolocation to recommend supermarkets that are near the user and Data Mining to recommend shopping lists based on the user's interests.
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  • IoT Watercare: Water Quality Control System in Unofficial Settlements of Peru Based in an IoT Architecture

    Salgado, Juanelv; Pizarro, Cesar; Wong, Lenis; Castillo, Jose (IEEE Computer Society, 2022-01-01)
    Many homes in the country of Peru, especially those located in unofficial settlements, are not connected to public service networks, and in the case of residential water, require tanker truck delivery. However, this water has often been contaminated from the upstream storage, conveyance and delivery systems that provide it, and thus will not comply with government water quality standards, ultimately compromising the health of the people who rely on it. While the topic of quality monitoring in traditional water networks has been studied, research has not focused on water quality control in under-developed and under-served unofficial settlements. This study introduces an IoT architecture and web-based system for real-Time monitoring of the key water quality parameters to help municipalities and other government entities to act early when large volumes of low-quality water are detected. The system proposed was implemented across five layers: capture, communication, processing, storage and presentation. Two experiments were conducted in a residential home with real time measurement of temperature, turbidity, TDS y pH. When comparing the results of both experiments, the pH parameter had a better precision with a 2% error rate. In addition, the survey results showed that the experts agree with the proposal.
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  • Mobile Application: A Serious Game Based in Gamification for Learning Mathematics in High School Students

    Ortiz, Willington; Castillo, Diego; Wong, Lenis (IEEE Computer Society, 2022-01-01)
    In the present study, a serious game based on gamification techniques was developed to motivate the learning of mathematical topics seen in the last academic grade of Peruvian high schools. The proposed game was developed for mobile devices and uses a cloud-based web infrastructure. In addition, gamification techniques such as avatar, levels, progress indicators and rewards were used for its design. A total of 14 students participated in the experiment and qualitative data were collected through a questionnaire. The results showed that the selected gamification techniques were very effective in motivating learning, the serious game had a good user experience, and the students were satisfied with the learning experience of the game.
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