International Conference on Applied Technologies

This article analyzes the influence of driving maneuvers on a hybrid vehicle's energy consumption and emission rates. Employing data collected through OBD II and GPS technologies, route variables are meticulously documented following the EURO 6 standard, primarily for assessing pollutant levels within a Real Driving Emissions (RDE) cycle, facilitated by the use of a Portable Emissions Measurement System (PEMS). Throughout the study, we identify key variables that exhibit the strongest correlation with fuel consumption, including Longitudinal acceleration (Ax), Torque, Accelerator pedal open position (APS), and engine speed (RPM). These variables enable us to discern the Internal Combustion Engine's (ICE) operational conditions and devise a model that accurately estimates the rate of fuel consumption change concerning vehicle acceleration. Furthermore, we classify driving modes as ecological, RDE, or aggressive based on the State of Charge (SOC) of the vehicle. Our findings reveal that the type of driving conducted on the road and city altitude directly influence fuel consumption and emission factors (CO₂, CO, HC, and NO_x). Notably, we observe a remarkable 31.36% reduction in fuel consumption during ecological driving compared to aggressive driving.

This article provides an SLR, or systematic review of the field of study known as “e-grocery adoption.’’ It suggests using grocery apps or online buying groceries to enhance marketing research. The purpose of this study is to critically revise and produce an essay about the adoption of grocery applications. 38 studies were produced by the SLR and presented concurrently to the adoption of grocery apps. Results from ahead descriptive analytics show the most important research questions around the adoption of grocery applications as well as diverse strategies that link researchers and participants in various research methods. The essay looks into the factors that led to the acceptance of grocery applications. The writers emphasized how the subject has evolved over time and noted the prospective potential future research topics. The study eventually provides references for further research on adoption of grocery applications.

The impact of green logistics in e-grocery on customer purchase behaviour is investigated in this study. Businesses that have implemented green logistics are seen as being successful in influencing customer product choices. Businesses are sensitive to shifting customer preferences and environmental conditions, and a factor that may have an impact on consumer purchasing behaviour is whether or not they embrace green logistics in line with their growth objectives. As a result, “acceptance of the green principle” develops into an international and societal phenomenon. Consumers consider the product's environmental effect in addition to its performance and quality when assessing a good or service. Businesses adopted the green idea as a result of realizing this, their duties regarding environmental impact, their quest of competitive edge, and their goal to enhance the marketability of their brands. The importance of R&D research has been acknowledged in this respect, and related efforts have increased. Overall, these actions improved living circumstances while lowering lifetime expenses. Consumer awareness of green brands has risen. Technology's usage in grocery delivery has increased e-grocery and integrated into everyday life. In this regard, it is important to ascertain if consumer environmental consciousness in e-grocery has an impact on channel choice. The adoption of green logistics is greatly influenced by consumer environmental awareness and needs, and green logistics practices in e-grocery have an impact on consumer purchasing behaviour, according to study findings on the impact of green logistics practices on the buying behaviour of enterprises. At this stage, a green strategy to domestic or global business activity has been demonstrated and must also be put into practice.

E-Participation provides a means to involve citizens in e-government decision-making. The ease of access to e-Participation processes has raised the issue of trustworthiness of both the institutions promoting processes and the citizens participating in these processes. Trust is an important factor influencing all human decisions consciously or unconsciously. This also applies to decisions to engage in e-Participation activities. Trust is perceived as a complex construct and is influenced by various factors. Consequently, different factors have to be taken into account in an e-Participation activity. While trust in ICT applications, such as e-commerce and social media networks, has been widely studied, trust in e-Participation has not been studied in depth. Since it is necessary to create a trusted environment so that citizens choose to participate in e-Participation processes, this paper analyzes the factors that directly influence trust in e-Participation initiatives through an empirical research. Based on the model of trust for e-Participation by [1] the influence of “Technology” and “Participatory Processes” on trust and the decision to engage in an e-Participation is investigated by means of a systematic literature study together with an empirical study. The online survey was conducted in cooperation with the cities of Bonn (Germany) and Valencia (Spain). The study analyzes predominantly the factors that influence the procedure, the technology, and the perceived risk and/or the benefits of the electronic participation. The analysis of the variables and their effects is carried out by the use of the “Structural Equation Modeling” and “Partial Least Squares” method. The result of this study reveals an influence of the investigated variables related to trust in technology and participatory processes of an e-Participation which leads to corresponding design recommendations for optimization of trust in e-Participation regarding technology and participatory process.

The objective of this study was to determine the agreement with the quality parameters of MOOC courses offered by the Open Campus initiative. It begins with an analysis of related literature that allows us to gather a Ten-Dimensional Model that presents quality and pedagogical guidelines for the design of this type of course and the 7Cs Learning Design Framework. In addition, the extent to which the participants evaluated the courses they had taken was analyzed by responding to a satisfaction survey. Quality criteria and compliance mapping were performed for a selected group of courses. Likewise, data from the satisfaction survey were analyzed to consider the opinions of the participants who took the courses. The results were analyzed based on the selected models. Finally, the level of compliance and the aspects to be improved that should be addressed by those who integrate the development teams of massive open online courses were determined.

Existing educational games for second language learning often lack consideration for a crucial aspect of the learning process: emotions, since these can influence the motivation and comprehension of the student. This study explores the application of affective computing as a complement to a gamified educational application, aiming to provide tailored feedback aligned with the student’s current emotional state. The implemented emotion detection model classifies users into four categories: satisfied, engaged, bored, and confused, then feedback is given according to the result of this model, which may include a comment on the content, an emotional one to re-integrate the student, or both to provide additional assistance, depending on the given scenario. To test this system, an experiment was conducted in a classroom, the results of which showed an effectiveness of the emotions model of 81.25%; moreover, with the use of a usability metric for gamified applications, it was obtained that in terms of the system Usability, there is an 84.87% efficiency, in Educational Usability there is an 85.71% effectiveness, in User Experience, there is a 75.24% of user satisfaction.

Gamification strategies are proved to motivate students while helping them develop the key skills related to a particular subject, especially when work- ing in virtual environments. During gamification students move forward, and go up levels while the learn new concepts. This research, is bases on the application of gamification strategies in the subject of Digital Thinking at the Universidad Autónoma de Perú. This was done through a quasi- experimental methodology. Among the main results there can be mentioned that the students felt more motivated, getting a more meaningful learning process.

The necessity to integrate training processes related to the development of Digital Competence (DC) levels has received widespread support in the field of education. However, it is important to emphasize that the definition of these levels may vary depending on the context and the tools employed. The design of initiatives to enhance these skills is influenced by the depth of the study, the approach taken, and the research methods utilized. This research aims to underscore the advantages of a mixed methodological approach, demonstrating how methodological and data triangulation enhances studies in this domain. A mixed methodological approach based on the Explanatory Sequential Design (ESD) was selected for conducting this study. This approach has allowed for a more profound and rigorous comprehension of the phenomenon, thus yielding a comprehensive perspective on it. Methodological and data triangulation has enriched the research by considering diverse viewpoints and approaches, offering a coherent, holistic, and thorough understanding of the subject matter. In the future, we propose the incorporation of data triangulation as an integrated methodology within the technological research ecosystem.

The combustion of polluting materials in industrial processes and motor vehicles, among other factors, causes atmospheric pollution that gradually degrades human health. Thus, air pollution monitoring has become an essential requirement for cities worldwide. However, traditional fixed monitoring stations present challenges in terms of cost and installation difficulty. In this context, monitoring solutions based on emerging technologies such as the Internet of Things and embedded systems have shown increasing interest. In this article, SPARKS-AIR, a low-cost fixed solution for air pollution monitoring, is described. SPARKS-AIR combines the design of an electronic board with a Raspberry Pi. The board allows connecting of up to six electrochemical gas sensors manufactured by Alphasense. The collected data is stored in a local database and sent directly to the cloud. The solution has been deployed in Manta, Ecuador, to validate our proposal. Our purpose is to analyse the behaviour of the solution in two areas of high vehicular traffic. In particular, we monitor and analyze the levels of Carbon monoxide (CO), Sulfur dioxide (SO\(_2\)), and Nitrogen dioxide (NO\(_2\)). Experimental results show that, in the two target locations, the hour associated with the highest pollution levels is 10 am. In addition, we observed that the values obtained for NO\(_2\) exceed the permitted thresholds by 200%, according to the World Health Organization (WHO).

There is a pattern that prevails in the music business for a long time. An artist writes, records, produces, and distributes a song so that the public can listen to it, and thus acquire financial compensation. This marketing and distribution effort is done collaboratively with record labels and companies that know the music business, because the artist alone cannot achieve a large audience. Because the actors involved in this process are too many, the main author gets the smallest percentage of the benefits. For this reason, this research proposes a model to support the music streaming service using blockchain-based smart contracts. For this, a prototype based on smart contracts is developed so that the author exhibits his musical works and gets an economic benefit. Using a web interface, a user can listen to a song by recording a monetary transaction within the blockchain. Consequently, this proposal allows a direct relationship between creators and consumers of musical content. Thus, blockchain was used to eliminate intermediation and directly reward the profits to the author of the melody. Conclusions and future work were presented at the end of the paper.

The dynamic and uncertain nature in which IoT systems operate has led to the exploration of new emerging Software Engineering approaches, such as self-adaptation, to provide these systems with autonomous capabilities to adjust their behavior at runtime to environmental changes. There are numerous primary studies on self-adaptation in IoT; however, it is necessary to deepen and update the state of technological knowledge in this area, especially in aspects that have not been addressed in previous reviews. Therefore, this paper presents a systematic review of the literature on self-adaptation in IoT systems, according to the guidelines proposed by Kitchenham et al. and the self-adapting topology created by Krupitzer et al. This review aims to answer the following research questions: i) In what context has self-adaptation been used in the IoT domain? ii) How is self-adaptation performed in IoT platforms? and iii) What is the research approach in studies related to self-adaptive systems in IoT? First, 1136 primary studies were obtained through automatic and manual searches. Then, inclusion and exclusion criteria were applied to select 84 relevant studies on self-adaptation in IoT. Finally, quantitative and qualitative methods based on extraction criteria were used to synthesize the strengths and weaknesses of the studies concerning the research questions as well as to identify research gaps and opportunities.

Equal opportunities in the learning process must become a priority in higher education institutions, where a hands-on approach enhances the training of the students. This research aims to present a virtual Internet of Things (IoT) sensor network to improve online education through a low-cost virtual IoT laboratory. This modular solution uses virtualization to replace hardware platforms, enabling the configuration of virtual nodes at the software level. This proposal combines Virtual Machines (VMs) to create a virtual network infrastructure, configuring each VM as a network device. Thus, there is no need for a large budget to implement hands-on approach laboratories in undergraduate and graduate degrees. Undergraduate technological students of the Instituto Superior Tecnológico Daniel Álvarez Burneo (ISTDAB, abbreviation in Spanish) validate the modular solution in the Network Security subject in the Technology Degree in Network and Telecommunications. A laboratory practice establishes the guidelines for mounting the virtual IoT sensor network. Finally, a satisfaction survey submits the acceptance of the proposal in the academic period (October 2022 - March 2023). Furthermore, the information provides evidence of the flexibility of the modular system in different scenarios.

Mortgage loans in financial institutions have evolved thanks to digital transformation, employing emerging technologies to streamline their processes, enhance customer service, and improve the customer experience. This research presents an enterprise architecture considering the development of its three domains: business, applications, and technology, for the financial institution under study. Additionally, we present technological solutions to manage customer verification, pre-qualification, credit assessment, and property evaluation. The proposal and its technological solutions include the enhancement of the mortgage loan lending process in terms of management, reduction of manual tasks, in-person activities at branches, and document submission for credit and property evaluation. In this regard, we use TOGAF and its ADM development methodology. Finally, the model was evaluated based on 5 dimensions with a panel of experts using the Delphi technique, resulting in a 94% acceptance level and a total of 17 items that achieved a high level of consensus. This indicates that the implementation of the model will help optimize the mortgage loan process.

Education is fundamental for all children, but those with neurological disorders, such as attention deficit hyperactivity disorder (ADHD), have specific learning needs that are not addressed by traditional educational methods. This project focuses on the creation of a mobile application that employs machine learning algorithms to evaluate the progress of these children through regression methods, focusing on mathematical problem solving in elementary schools in Lima. Results have shown that this initiative has improved the understanding and performance of children with ADHD, highlighting the potential of mobile technology and machine learning to move towards a more inclusive and effective education for this group of students. This project has proven to be a valuable tool in the educational field. The inclusion of technological tools such as the mobile app has allowed personalization in teaching, adapting the content and pace of learning to the individual needs of each student with ADHD. In addition, the use of machine learning has enabled a continuous and accurate monitoring of their progress, identifying areas for improvement early on.

In the evolving landscape of construction safety management, the integration of Internet of Things (IoT) and Building Information Modeling (BIM) technologies [1] presents a novel approach to addressing the dynamic challenges of workplace safety. The MANTRA project, developed under the ASSIST-IoT H2020 (Horizon 2020) project [2], introduces an innovative hybrid mobile application designed to enhance the safety of construction workers by providing real-time, interactive visualization and management of temporary danger zones on construction sites.

This paper outlines the development and implementation of MANTRA, focusing on its integration of BIM for detailed site representation and ASSIST-IoT platform for real-time data exchange and alerts management. The application enables workers to identify and mark danger zones directly on digital site models, significantly improving the timeliness and accuracy of safety warnings. By leveraging cross-platform compatibility through Progressive Web App (PWA) Framework [3], MANTRA ensures widespread accessibility and usability.

Preliminary results from field tests and lab evaluations demonstrate MANTRA’s effectiveness in improving situational awareness and reducing the risk of accidents. The application not only streamlines the process of marking and communicating hazards but also promotes a proactive safety culture.

MANTRA’s contribution to construction safety represents a significant advancement in digital technology application, highlighting the potential for IoT and BIM integration in risk management and worker safety enhancement in dynamic work environments.

The present research conducts an experimental study with a qualitative approach to the event management of an SDN network. To this end, a conceptual model of event monitoring in SDN networks is proposed that tests the usefulness of Camunda in the handling of multiple events in a network. Also, different scenarios are proposed where the event-driven architecture (EDA) intervenes through services to obtain information from the network and create instances of decision flows in the BPM. The results obtained show a dynamic, robust, and scalable solution for event handling. Camunda's tools make it easy to condition the flow, implement new processes in which different BPM instances are involved, and define the execution time of each event, among others. In addition, BPM scenarios allow you to add an integration layer that contains HTTP libraries for execution and XSLT Saxon API libraries for request and response transformations from external APIs. Finally, an integration interface is implemented capable of formatting the message according to an XSLT template that is then sent to another platform via API-Rest. This interface opens the possibility of new studies related to the definition and execution of multiple services through dynamic criteria, according to the information from an SDN event.

Cloud-based Enterprise Resource Planning (ERP) solutions have become integral for modern organizations seeking scalable and flexible business processes. However, the secure and compatible integration of these solutions poses significant challenges. This survey paper comprehensively reviews existing literature to identify key security and compatibility issues in Cloud-based ERP integration. The paper explores strategies, best practices, and emerging trends to address these challenges, providing valuable insights for researchers and practitioners alike.

The aim of this research was to describe the bibliometric and engineering aspects regarding the role of big data impact on organizations in the 21st century. In this sense, a search was initiated in several scientific databases such as: Scopus, DOAJ, Dialnet and Aerospace Database; using the following keywords: Big Data, Innovation Strategy, Company, Quality improvement, Competitiveness, Value of information, Industry 4.0, Sustainability and Information System. Subsequently, inclusion and exclusion criteria were applied corresponding to the presence of the study variable in the title, article, year of publication, publication in open Access, type of research, quantitative results of the study, among other criteria. The bibliometric results showed that during the years 2013–2022 the productivity of the company was increased by updating its methodical system, 80% of identified studies have been published in English and 20% in Spanish, while Scopus, DOAJ and Dialnet are the databases with the largest amount of research on this topic. In the case of the results, tools associated with the impact of big data on entities and the most outstanding effects achieved with its implementation were identified. Finally, it was concluded that the impact of big data in organizations represents a great development for companies due to its positive impact on decision making, optimization and innovation.

The CONTINGENT project, developed under the CYRENE H2020 (Horizon 2020) project [1], is a pioneering initiative by FAVIT [2] to bolster cybersecurity in evolving Information and Communication Technologies (ICT) systems. The project’s focus is on enhancing cyber resilience through advanced Machine Learning (ML) techniques, addressing the increasing need for robust cybersecurity solutions in various sectors like transport, healthcare, and energy.

CONTINGENT aims to develop and deploy a suite of cybersecurity services/products for Supply Chain Services, utilizing HoneyPots (HPs) and Digital Twins (DTs) [3] to gather rich, actionable data [4]. These tools simulate vulnerable services, attracting and analyzing potential cyber threats. The collected data feeds into ML algorithms, enabling real-time analysis and identification of unknown attack patterns, ensuring proactive defense against cyber threats.

The proposed solution includes a set of docker containers with configurable HP services and ML models, integrated within the CYRENE platform. This integration will facilitate seamless data sharing and visualization through CYRENE’s dashboard, enhancing overall cybersecurity measures.

Through CONTINGENT, FAVIT addresses significant technical challenges, including managing vast log data, ensuring easy integration across environments, and adhering to CYRENE’s guidelines. This project represents a significant step forward in securing ICT systems against evolving cyber threats, ensuring the resilience and safety of critical infrastructures and data.

According to a study conducted by UNICEF, the main causes of childhood obesity are the high consumption of processed foods and the low amount of physical activity performed by children, generating a higher risk of respiratory, metabolic and cardiovascular conditions. Based on research conducted in different studies, we found that there are not many technologies that monitor and improve the physical performance of children. This paper presents a technological system based on IoT and using wearables to improve the physical performance of children with high obesity rates type 1 and 2. This technological system was verified by conducting a study with 30 children between 4 and 8 years old, evaluating their physical activity and collecting the data obtained from the smartwatch. This study showed, according to the conclusions found, that it is a useful tool for the collection of data required by specialists and easy to use for children and their parents. In addition, it is a means to overcome the obesity problem.

Peru has a fragmented health system, which limits access to its health services because the people seeking medical services can only be treated in specified health centers that are determined by their health insurance. Additionally, this causes each health provider to count and manage their processes and information in an isolated and independent manner. In the Peruvian case, this generates an overload in public health services, since, of the 83.3% of insured nationwide, 73.1% belong to the public sector. Therefore, a process architecture is presented, based on the Zachman framework, that integrates the processes of health services (outpatient, hospitalization and emergencies), as well as an Information Technology (IT) process that supports them. The architecture aims to ensure that level III hospitals in Peru have standardized processes and information, as well as to guarantee their application regardless of the hospital regime. The processes were designed based on information from two Peruvian level III hospitals, belonging to the Sistema Integrado de Salud (SIS) and Seguro Social de Salud (EsSalud). A time simulation of the current processes and those proposed by the architecture, show an average improvement percentage of 69% in the outpatient process, 27% in emergencies and 7% in hospitalization. In addition, an expert judgment was made obtaining a very high assessment on the usefulness of the architecture.

Burnout is a professional mental health syndrome marked by exhaustion, growing detachment from work, and decreased work efficiency. It can lead to serious consequences for physicians, including medical errors, legal disputes, substance abuse, and suicidal thoughts. This study aimed to assess the prevalence of Burnout Syndrome among doctors in a tertiary hospital in Guayaquil. Utilizing the Maslach Burnout Inventory (MBI-HSS) assessment tool, it was found that 21.8% of the 78 doctors surveyed met all criteria for Burnout Syndrome. Notably, male physicians exhibited more pronounced signs of burnout than their female counterparts. This underscores the importance of personalized interventions and a holistic understanding of workplace challenges, especially in high-pressure environments like healthcare. Future policies and workplace reforms should address these issues to ensure both the well-being of medical professionals and the quality of patient care.

In this paper, we give the main focus on the continuous advancement in the field of wind energy. Public make great attention towards the renewable energy because of rapid increase in energy demand, cost increase in electric power, limited reserves of energy, and adverse environmental impact by fossil fuels etc. At the same time on the other hand, latest technology, available low cost materials, and governmental incentives. Wind energy is one of the ultimate clean and sustainable source of energy on the Earth. By above reasons, wind become a fastest growing renewable energy resource. Here maximum power technique of wind turbines with the help of generator are used to generate electric power from wind. Here thirty three publications are given on the same topic for the quick reference to researchers.

The COVID-19 disease is caused by SARS-CoV-2, which has caused an unprecedented health, economic and social crisis, globally and regionally. The objective is to identify the main adverse effects of the Covid-19 vaccination in the workers of a construction company in the city of Guayaquil-Ecuador, through Google drive forms where a questionnaire was applied that was answered individually by a sample of 215 workers of a construction company in Guayaquil. The results indicated that the symptom that predominated in this dose or booster dose was the third pain in the injection area with 14.4% and fatigue with 12.6%. 61.4% do not present any symptoms. During this year and a half since vaccination for Covid-19 began, the vaccines used to reduce serious illness have proven to be safe and effective regardless of the name of the vaccine.

This study is based on the proposal of a mathematical model that allows to know the amount of Biochemical Oxygen Demand (BOD) at the outlet of a wastewater treatment plant, to achieve this multivariate regression will be used as a strategy to obtain the parameters of the mathematical model. For this, a subjective characterization of the main variables involved in the treatment process of the wastewater plant was carried out, taking into account the information provided by the company, discriminating between the variables that do not add value and those that are derived from others. The type of method used is quantitative and the technique used to collect the information was primary. Then we proceeded to formulate the mathematical model using multivariate regression and for this the SPSS software was used, then we continued with the validation of the model, to achieve this we used the criterion of the assumptions of multivariate regression which are: assumption of normality, assumption of correlation of variables, assumption of multicollinearity, assumption of independence of errors, assumption of homoscedasticity, assumption of normality of waste. As a result and analysis of the present research, it was concluded that the mathematical model obtained is acceptable since it complies with the regression assumptions, the value of R-squared is acceptable.

In this paper, we give the main focus on the comparative study on Modern Techniques used for Maximum Power Extraction of Solar and Wind Energy Systems. A prototype model has been made for Solar and Wind, Results are compared with lookup table. We have also discuss regarding advantages, disadvantages and applications of renewable energy. 26 publications on this topic are here for the quick reference.