In the current digital era, efficiently accessing relevant information is crucial for various applications such as restaurant recommendation systems, website searches, book recommendations, among others. This study presents an approach for personalized recommendations in improving the customer service process in restaurants using OpenAI's Contextual Chatbot. The approach consists of six phases: (1) Data preprocessing, (2) Embedding and storage, (3) Scheduled updating, (4) Document retrieval, (5) Context adaptation and request creation, and (6) Response generation. OpenAI's text embeddings are used to convert application data into vectors and store them in a vector database. These vectors are used to retrieve similar records and generate contextualized responses using the GPT-3.5 model. The chatbot's performance is evaluated in terms of accuracy and user satisfaction. Two scenarios were used in the experimentation: (a) with the proposed solution and (b) without the solution. The results demonstrated an operational efficiency of 86.67% with the proposed solution and the versatility of the proposed methodology, showcasing its potential for application in a wide range of domains, including websites, books, PDFs, and other forms of documentation.

In recent years, significant progress has been made in the integration of technologies in voting systems with the aim of improving the transparency of the process. This study proposes an audit model based on the ISO/IEC 27002 standard to evaluate electronic voting systems that make use of Blockchain technology and the Internet of Things (IoT), with the aim of improving security in voting processes. To validate this model, an evaluation of the security control was carried out by applying this international standard to a voting system that integrates Blockchain and IoT. In our analysis of 6 security controls applied to the reality of electronic voting, the system passed all established tests; Therefore, it can be concluded that the risk of compromising system information has been significantly mitigated. This research contributes to the advancement of the security of electronic voting systems and provides a solid foundation for future developments in this field. The combination of emerging technologies and international standards promotes trust, security and therefore mitigates any risk of compromising an electronic voting system by following the best practices of the international standard ISO/IEC 27002.

In Metropolitan Lima, small and medium-sized enterprises (SMEs) face significant challenges in obtaining financing, primarily due to high interest rates and stringent requirements from traditional financial institutions. This research introduces a crowdlending system based on smart contracts backed by blockchain technology as a solution to these obstacles. A validation with end users was conducted, and the results obtained demonstrated an impressive compliance rate of 99%. This innovative approach provides a secure, transparent, and efficient environment, offering a robust solution to the financing needs of SMEs in the region.

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).

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.

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.

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.

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.

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.

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.