Use Of Tool Research Articles

User-centric AI: evaluating the usability of generative AI applications through user reviews on app stores

This article presents a usability evaluation and comparison of generative AI applications through the analysis of user reviews from popular digital marketplaces, specifically Apple’s App Store and Google Play. The study aims to bridge the research gap in real-world usability assessments of generative AI tools. A total of 11,549 reviews were extracted and analyzed from January to March 2024 for five generative AI apps: ChatGPT, Bing AI, Microsoft Copilot, Gemini AI, and Da Vinci AI. The dataset has been made publicly available, allowing for further analysis by other researchers. The evaluation follows ISO 9241 usability standards, focusing on effectiveness, efficiency, and user satisfaction. This study is believed to be the first usability evaluation for generative AI applications using user reviews across digital marketplaces. The results show that ChatGPT achieved the highest compound usability scores among Android and iOS users, with scores of 0.504 and 0.462, respectively. Conversely, Gemini AI scored the lowest among Android apps at 0.016, and Da Vinci AI had the lowest among iOS apps at 0.275. Satisfaction scores were critical in usability assessments, with ChatGPT obtaining the highest rates of 0.590 for Android and 0.565 for iOS, while Gemini AI had the lowest satisfaction rate at −0.138 for Android users. The findings revealed usability issues related to ease of use, functionality, and reliability in generative AI tools, providing valuable insights from user opinions and feedback. Based on the analysis, actionable recommendations were proposed to enhance the usability of generative AI tools, aiming to address identified usability issues and improve the overall user experience. This study contributes to a deeper understanding of user experiences and offers valuable guidance for enhancing the usability of generative AI applications.

Assessment of Digital Tool Impact in Language Education: Insights from Educators and Students

This study evaluates the implementation and impact of digital educational tools in foreign language classrooms from both educators' and students' perspectives in Serbian secondary schools before, during, and after the COVID-19 pandemic. The research investigates the digital tools used, the challenges faced, and the perceived benefits of these tools in enhancing teaching and learning experiences. Quantitative data were collected through online surveys administered to 173 language teachers and 126 fourth-year secondary students, focusing on their experiences with digital tools in various instructional models—traditional, online, and hybrid. Results reveal significant discrepancies between teachers' and students' perceptions of digital tool usage and its frequency. While the majority of teachers reported frequent use of digital tools, students indicated less frequent exposure. Key findings indicate that digital tools like Google Classroom, Kahoot!, and Quizziz were widely used during the pandemic and continued to be utilized post-pandemic. Teachers highlighted the need for comprehensive training in digital competencies to integrate these tools into their teaching practices effectively. Both educators and students acknowledged the benefits of digital tools in creating dynamic and engaging learning environments, yet challenges such as maintaining student motivation and balancing attention in hybrid models were noted. This study underscores the importance of aligning training programs with teachers' needs and suggests future research to assess the effectiveness of such programs and explore non-technology-related factors influencing digital tool adoption in foreign language teaching.

Unusual Composition of the Sarezzano Reliquary Busts

The interdisciplinary study of two reliquary busts from Sarezzano (Piedmont, Italy) is a perfect example of the necessity to provide for material characterisation as a recurring common practice in historical studies and a mandatory step in conservation assessment. Furthermore, the diagnostics of cultural heritage play a crucial role in art historical research, providing relevant information on artefacts’ genesis, production technology, and conservation history. The study of the materials of the reliquary busts was performed by non-invasive (portable X-ray fluorescence spectrometry) and micro-invasive (stereomicroscope, attenuated total reflection Fourier transform infrared spectroscopy and powder X-ray diffraction analysis) methods. According to the results, the busts were found to be made of a tin–lead alloy, a rather unusual material for mediaeval reliquary busts. Moreover, the outcome suggests that the busts were originally silvered, except for the hair and beard which are still gilded. The analysis reveals the use of colophony as an adhesive buffer layer on the busts’ alloy, as well as inside them, to favour the metal working process, since it is found as degraded residue. Finally, even the typology of alloy decay is defined. All this information has enabled us to determine the artistic technique and estimate the value and quality of the material employed. In addition, it has led to the correct choice of materials and methods to be adopted during the restoration, and therefore the usage of more suitable solvents and tools.

Artificial intelligence in healthcare: a scoping review of perceived threats to patient rights and safety

BackgroundThe global health system remains determined to leverage on every workable opportunity, including artificial intelligence (AI) to provide care that is consistent with patients’ needs. Unfortunately, while AI models generally return high accuracy within the trials in which they are trained, their ability to predict and recommend the best course of care for prospective patients is left to chance.PurposeThis review maps evidence between January 1, 2010 to December 31, 2023, on the perceived threats posed by the usage of AI tools in healthcare on patients’ rights and safety.MethodsWe deployed the guidelines of Tricco et al. to conduct a comprehensive search of current literature from Nature, PubMed, Scopus, ScienceDirect, Dimensions AI, Web of Science, Ebsco Host, ProQuest, JStore, Semantic Scholar, Taylor & Francis, Emeralds, World Health Organisation, and Google Scholar. In all, 80 peer reviewed articles qualified and were included in this study.ResultsWe report that there is a real chance of unpredictable errors, inadequate policy and regulatory regime in the use of AI technologies in healthcare. Moreover, medical paternalism, increased healthcare cost and disparities in insurance coverage, data security and privacy concerns, and bias and discriminatory services are imminent in the use of AI tools in healthcare.ConclusionsOur findings have some critical implications for achieving the Sustainable Development Goals (SDGs) 3.8, 11.7, and 16. We recommend that national governments should lead in the roll-out of AI tools in their healthcare systems. Also, other key actors in the healthcare industry should contribute to developing policies on the use of AI in healthcare systems.

Usability of a digital tool to support long-lasting insecticide net distribution in Northern Bahr el Ghazal State, South Sudan.

Long-lasting insecticidal nets (LLINs) have been a widely used malaria prevention method for decades. In South Sudan, LLINs are typically distributed by volunteers who use paper-based systems to collect distribution data. Paper-based systems are simple to use but have a higher occurrence of data inaccuracies and can hinder the timely use of data for decision-making. In 2022, a digital tool was introduced to collect data during the LLIN campaign in Northern Bahr el Ghazal (NBeG). The tool aimed to improve the accuracy of data entry and enable data to be used in real-time for decision making during the campaign. The digital tool was developed with offline functionality and interoperability with DHIS2 tracker version 2.8 in DHIS2 version 2.38. This study assessed the usability of the tool according to user perspectives. A questionnaire containing open- and closed-ended questions was conducted with users of the digital tool, supervisors and other key stakeholders in five counties of NBeG. The questionnaire was administered using Malaria Consortium's Projects Results System Android mobile application. Usability was determined through a modified and validated System Usability Scale (SUS) approach. A total of 93 participants responded to the usability questionnaire. The mean (± standard deviation) usability score across 10 SUS-scoring items was60.91 (12.87), indicating a modest level of usability. The majority of users agreed the tool was useful for managing the LLIN distribution workflow, was easy to use, reduced workload, and supported stock management and real-time campaign monitoring. There was no significant difference in the usability scores across genders, roles, and counties. Respondents with experience of both paper-based and the digital tool tended to express a preference for the digital tool over paper-based systems. The majority of respondents also reported they would recommend the digital tool to colleagues. Digital tools are perceived to improve data collection during LLIN campaigns, even in remote areas where network coverage is challenging. Additional improvements can be implemented to overcome operational challenges and improve usability of the tool. Further study is needed to assess the impact of the digital tool on data quality and real-time data use.

SAPPNet: students’ academic performance prediction during COVID-19 using neural network

A variety of reasons have made it more difficult for educators and tutors to anticipate students’ performance. Numerous researchers have used various predictive models to identify students who may be at-risk of dropping out early. Additionally, these methods were used to forecast final semester grades based on various datasets. However, these prediction models still fall short of meeting educational management requirements. In this paper, we propose the deep learning (DL) based model named students academic performance prediction network (SAPPNet) to predict the students’ grades. We consider the questionnaire-based Jordan University dataset which contains demographic information, usage of digital tools before and after COVID-19, sleep times before and after COVID-19, social interaction, psychological state, and academic performance. SAPPNet consists of spatial convolution modules which are designed to extract spatial dependencies includes categorical and numerical attributes that represent static features (gender, level/year, age, digital tools used before and after COVID-19, psychological condition using prolonged e-learning tools) and temporal module for temporal dependencies involves sequences that capture changes before and after COVID-19. Additionally, we also try to implement classical machine learning (ML) models including support vector machine, k nearest neighbor, decision tree, and random forest, and DL models named artificial neural network, convolutional neural network, long short-term memory, and students learning prediction network. Simulation results show that SAPPNet achieved the best performance compared to state-of-the-art methods, with an accuracy, precision, recall, and an F1-score of 93%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$93\\%$$\\end{document}. The proposed model with spatial and temporal modules improves the prediction performance, and it implies new aspect of the educational dataset.

Conducting Patient-Oriented Research in Pediatric Populations: A Narrative Review.

It has become increasingly common for researchers to partner with patients as members of the research team and collaborate to use their lived experiences to shape research priorities, interventions, dissemination, and more. The patient-oriented research (POR) model has been adopted by both adult and pediatric health researchers. This cultural change to conducting pediatric health research brings with it new methodologies, tools, challenges, and benefits. In this review, we aim to provide guidance on how to conduct POR for pediatric populations using examples from the literature. We describe considerations for engagement before the project begins, for engagement across the research cycle, and for measurement and evaluation. We aim to show that conducting POR is feasible, beneficial, and that many common challenges and barriers can be overcome with preparation and usage of specific tools.

Evaluating User Experiences and Preferred Features of a Web-Based 24-Hour Dietary Assessment Tool: Usability Study.

Intake24, a web-based 24-hour dietary recall tool developed in the United Kingdom, was adapted for use in New Zealand (Intake24-NZ) through the addition of a New Zealand food list, portion size images, and food composition database. Owing to the customizations made, a thorough evaluation of the tool's usability was required. Detailed qualitative usability studies are well suited to investigate any challenges encountered while completing a web-based 24-hour recall and provide meaningful data to inform enhancements to the tool. This study aims to evaluate the usability of Intake24-NZ and identify improvements to enhance both the user experience and the quality of dietary intake data collected. We used a mixed methods approach comprising two components: (1) completion of a single 24-hour dietary recall using Intake24-NZ with both screen observation recordings and collation of verbal participant feedback on their experience and (2) a survey. A total of 37 participants aged ≥11 years self-completed the dietary recall and usability survey (men and boys: 14/37, 38% and women and girls: 23/37, 62%; Māori: 10/37, 27% and non-Māori: 27/37, 73%). Although most (31/37, 84%) reported that Intake24-NZ was easy to use and navigate, data from the recorded observations and usability survey revealed challenges related to the correct use of search terms, search results obtained (eg, type and order of foods displayed), portion size estimation, and associated food prompts (eg, did you add milk to your tea?). This comprehensive usability study identified challenges experienced by users in completing a dietary recall in Intake24-NZ. The results informed a series of improvements to enhance user experience and the quality of dietary data collected with Intake24-NZ, including adding new foods to the food list, optimizing the search function and ordering of search results, creating new portion size images, and providing clearer instructions to the users.

Development and Pilot Study of myfood24 West Africa—An Online Tool for Dietary Assessment in Nigeria

Background and objective: Tools to accurately and efficiently measure dietary intake in Nigeria are lacking. We aimed to develop and assess the usability of a new online dietary assessment tool for Nigeria—myfood24 West Africa. Methods: We developed the myfood24 West Africa database using data from existing food composition tables, packaged foods labels and research articles. The development followed seven steps: identified data sources, selected foods, processed/cleaned the data, calculated the nutrient content of recipes, created and allocated portion sizes, quality-checked the database and developed food accompaniments. To pilot the tool, we recruited 179 university staff in Nigeria using a cross-sectional design. Usability was assessed using a questionnaire that included the System Usability Scale (SUS) and a feedback session. Results: The database included 924 foods, with up to 54 nutrients and 35 portion-size images allocated to foods. Sixty percent of the data were sourced from the 2019 West Africa Food Composition Table, 17% from back-of-pack labels of packaged foods, 14% from the 2017 Nigerian Food Composition Table, 5% from generated recipes and 4% from the published literature. Of the participants, 30% (n = 53) self-recorded their food intake, with a total of 1345 food and drink entries from both self- and interviewer-collected data. The mean SUS score of 74 (95% CI: 68,79) indicated good usability. The feedback showed that the tool was user-friendly, educational and included a variety of local foods. Conclusions: This new tool will enhance the dietary assessment of the Nigerian population. More work will expand coverage to include more foods from the region.

Developing and evaluating an e-learning and e-assessment tool for organic chemistry in higher education

A convincing e-learning system for higher education should offer adequate usability and not add unnecessary (extraneous) cognitive load. It should allow teachers to switch easily from traditional teaching to flipped classrooms to provide students with more opportunities to learn and receive immediate feedback. However, an efficient e-learning and technology-enhanced assessment tool that allows generating digital organic chemistry tasks is yet to be created. The Universities of Bonn and Duisburg-Essen are currently developing and evaluating an e-learning and technology-enhanced assessment tool for organic chemistry. This study compares the effectiveness of traditional paper-pencil-based and digital molecule-drawing tasks in terms of student performance, cognitive load, and usability—factors that all contribute to learning outcomes. Rasch analysis, t-tests, and correlation analyses were used for evaluation, revealing that the developed system can generate digital organic chemistry tasks. Students performed equally well on simple digital and paper-pencil molecule-drawing tasks when they received an appropriate introduction to the digital tool. However, using the digital tool in two of three studies imposes a higher extraneous cognitive load than using paper and pencil. Nevertheless, the students rated the tool as sufficiently usable. A significant negative correlation between extraneous load and tool usability was found, suggesting room for improvement. We are currently concentrating on augmenting the functionality of the new e-learning tool to increase its potential for automatic feedback, even for complex tasks such as reaction mechanisms.

Identifying Differences in the Application of HR Marketing Tools in Companies in the Secondary Sector – a Case Study of Mining, Construction, and Manufacturing Industries

HR marketing is a relatively new field in corporate practice. When implemented effectively and designed professionally, HR marketing can give companies a significant competitive advantage in the labour market. Increasingly, HR managers and executives focus on securing high-quality and skilled employees who are integral to building a strong brand and employer value. To date, no studies have specifically examined HR marketing within the secondary sector, which appears to be stagnating in economically developed countries. This study aims to identify differences in the application of HR marketing tools among companies operating in the secondary sector, particularly within the mining, construction, and manufacturing industries. The research was conducted in two stages: the first stage involved an analysis of HR marketing practices among a sample of 215 companies operating in the Czech Republic and Slovakia. The second stage focused on a case study of 10 companies from the secondary sector, specifically three companies operating in the mining, construction, and manufacturing industries. This study offers a comparative analysis of HR marketing tool usage among companies within the secondary sector, including those in the Czech Republic and Slovakia. The key findings address the research questions and hypotheses. The results indicate that companies in the secondary sector primarily use traditional HR marketing tools such as company websites, personnel agency services, and job portals. Mining and manufacturing companies employ a wider range of HR marketing tools to enhance employee loyalty than construction companies.

Designing with words: exploring the integration of text-to-image models in industrial design

ABSTRACT This study investigates the effectiveness of Text-to-image (T2I) models in assisting industrial designers with the visualization of product concepts. Using action research and a reflection-in-action, this research conducts a series of experiments utilizing Stable Diffusion for generating chair concepts. The research findings are positioned within an existing framework of computational tools usage, and assess the quality of the generated images in supporting industrial design activities during the define and develop phases of the design process. While T2I models provide competent support to ambiguity and sketch improvement, their efficacy in generating coherent solutions for further development is limited. This study provides guidelines for the effective application of T2I models in industrial design practice. It discusses the T2I models’ suitability for specific design activities, addresses associated risks, and proposes a taxonomy of prompt modifiers that ensures a closer match between input prompts and generated product concepts.

University Students’ Attitudes and Perceptions towards AI Tools: Implications for Sustainable Educational Practices

The integration of artificial intelligence (AI) tools in educational settings offers significant opportunities to promote sustainability by transforming learning experiences. This study analyses the usage, attitudes, and perceptions of AI tools among university students in Slovenia providing a comprehensive analysis that informs both academic practices and policy-making with emphasis on sustainability. We used a structured questionnaire with a sample of 422 participants reflecting a diverse demographic profile across various fields of study. The questionnaire was designed to measure the frequency of AI tool usage, the purposes for which these tools are employed, and students’ attitudes and perceptions towards AI’s potential benefits and drawbacks in education. Statistical analyses, including Analysis of Variance (ANOVA), were utilized to test hypotheses concerning differences in AI tool usage based on the level and field of study. Findings reveal that students recognize the efficiency of AI, but express concerns about its impact on learning quality and academic integrity, emphasizing the need for a balanced and responsible integration of AI in education to achieve sustainable outcomes. Results indicated that a majority of students are engaging with AI tools, with varied frequencies of use largely dependent on their field of study and academic level. The findings suggest that while AI tools are becoming an integral part of the educational landscape in Slovenia, there is a critical need to address the educational, ethical, and psychological impacts of these technologies. The results highlight the necessity for further research into the educational implications of AI, suggesting a balanced and sustainable approach to integrating these technologies into higher education curricula. Such an approach ensures that the adoption of AI not only enhances learning outcomes but also aligns with the principles of sustainability, promoting long-term benefits for both education and society.

Translation and initial cross-cultural adaptation of the tool for support-gradual return-to-work for persons with chronic musculoskeletal pain to the Swedish setting.

A well-defined and clear procedure is a key factor supporting return-to-work and enhancing collaboration and understanding between employers and employees. The adaptation of the Tool for Support-Gradual Return to Work, TS-GRTW, addresses relevant cultural aspects valuable for wider adoption. develop a Swedish version, the GRTWswe, for implementation and integration into the Swedish labor market's RTW process. This involved translating, culturally adapting, and assessing the appropriateness and utility. In the initial step, a double back translation was performed to create an initial translated version. This version was then utilized in individual consultations, accompanied by an agreement questionnaire. For the subsequent step, group consultations were held to refine and customize the tool to suit the Swedish context. Ten occupational therapists completed the questionnaires, with mean agreement scores surpassing three on a four-point scale. Out of these, nine participated in group consultations. The findings suggest the requirement for specific modifications to the GRTWswe. These adaptations are essential because of cultural differences in organizational structures and reference frameworks. Moreover, participants unanimously agreed to broaden the scope of target groups, encompassing employees without regard for diagnosis and expanding the range of professions that can utilize this tool. This step aims to enhance the tool's applicability and usefulness. The study found strong alignment between questionnaire responses and group consultations outcomes, affirming the adapted tool's suitability for use in a Swedish context. The tool benefits employers and employees by enhancing communication, encouraging collaboration, and structuring processes, promising lasting improvements to work conditions.

The Good and Bad of AI Tools in Novice Programming Education

As AI coding tools become more prevalent in programming, it is essential to understand how they influence programming education. This study, conducted in a first-semester Introduction to Programming course, aimed to determine the positive and negative effects of these tools on students’ learning experiences and their ability to develop essential programming skills. Using a mixed-methods approach, we collected data from 73 teams of engineering students over a 12-week period. Students completed surveys and reported on their AI tool usage. We analyzed this data quantitatively to identify trends in tool familiarity, usage, and student satisfaction. Additionally, qualitative analysis of student reports provided insights into the specific ways AI tools were used and their perceived benefits and drawbacks. The findings revealed a significant increase in AI tool familiarity (from 28% to 100%) and usage among students. Students’ satisfaction with AI tools improved over time. The most prevalent tasks for which novice programmers used AI tools included creating comments (91.7%), identifying and correcting bugs (80.2%), and seeking information (68.5%), while other tasks were less common. While these tools offered benefits like assisting in learning and enhancing real-world relevance, they also raised concerns about cheating, over-reliance on AI tools, and a limited understanding of core programming concepts.

University EFL Students’ Perspectives on Educators’ Digital Competence at Qassim University

Personal and professional success in the digital age requires digital abilities. Increased expectations that graduates be adept in digitisation while joining the job need higher education institutions to successfully incorporate digital aspects. This study evaluates university EFL students' digital integrative attitudes and instructors' digital proficiency. Digital tools are emphasised for collaborative learning. Researchers seek to address two key questions: What are EFL students’ perspectives on digital learning? How do they assess teachers' IT skills? It appears through the end result not all instructos have the same digital competency and it is strictly field dependent. This variance in the digital capalities and field orientation decideis the choice of their preferredd pedagogical tools. Digital collaborative learning was used by both categories of students: engineering students and non-engineering EFL students to variable degrees. This suggests that punishing students may affect preferences and behaviours in this area. EFL students were confident in their digital tool usage, although they didn't comprehend all the features. This study's results may improve instructional techniques, institutional standards, and professional development programmes to improve educators' digital abilities. As digital technology integration evolves, global higher education consequences are enormous.

Integrating digitalization opportunities into innovative public organizations’ management process

The COVID-19 pandemic has had an impact on public institutions management system which imposed a digital transformation of all processes. This study explores how integrating digitalization improves management processes within Romanian public organizations. It is based on a survey approach and on “snowball” sampling technique for collecting answers from 377 employees. The analysis was developed with structural equation modeling (PLS-SEM), prediction-oriented segmentation (PLS-POS), and multigroup analysis (PLS-MGA). The obtained results show that the digitalization of public institutions has a positive effect on all five managerial functions, namely on planning, organizing, coordinating, motivating, and controlling. The findings revealed three distinct homogenous groups of respondents using a posteriori segmentation, presenting variations in tool usage and function execution. There are multi-faceted contributions of this study: (1) in terms of theory, as it contributes to the literature by reinforcing existing knowledge; (2) in terms of methodology as it employs triangulation, and (3) in terms of practical implications by offering insights for decision-makers aiming to enhance institutional dynamics in public administration, albeit within the limitations of its geographic focus. In the last part of the paper, future research directions for integrating digitalization within public institutions are presented.

Mobile Forensics Analysis for Instant Messaging Applications Namely TamTam and Botim

Cybercrimes are rapidly increasing in parallel with the usage of digital tools. Criminals can use many methods to carry out their crimes such as mobile phones and instant messaging applications. Because of that, it is important to investigate the ability to retrieve evidence from mobiles that may be involved in cybercrime. This research aims to perform a mobile forensic analysis to retrieve evidence from specific instant messaging applications. To this end, an experiment was conducted to mimic the scene of illegal messages, delete them, and investigate the ability to retrieve deleted files. According to the result, this research successfully obtained text messages, multimedia data, and contact lists. The research's novelty can be derived from its ability to retrieve deleted data, demonstrating the feasibility of retrieving evidence from instant messaging applications that have not been investigated before. In future work, analyzing these applications under other operating system platforms may offer valuable artifacts for investigators.

Exploring Chinese University Educators’ Acceptance and Intention to Use AI Tools: An Application of the UTAUT2 Model

Artificial Intelligence (AI) tools are having a significant impact on the field of education, particularly when used by educators. This study aims to explore the acceptance of AI tools among university-level educators. Researchers adapted the UTAUT2 (Unified Theory of Acceptance and Use of Technology) model to the Chinese educational context and surveyed 402 university educators. The findings revealed several predictors related to educators’ behavioral intention to use AI tools in teaching including performance expectancy, effort expectancy (which emerged as the strongest predictor), and hedonic motivation. Additionally, the study showed that the predictors of actual AI tool usage are facilitating conditions, habit (identified as the strongest predictor), and behavioral intention. Notably, the study found that gender, age, and experience did not have a moderating effect. This study contributes to the existing body of evidence on AI tool acceptance among university educators and holds implications for their training and professional development.

Redefining Hospital Accessibility: A Service Design Framework for Inclusive Healthcare

Abstract In the framework of becoming a carbon neutral city by 2030, Bologna faces challenges related to enhancing the quality and accessibility of its built environment to improve the quality of life and well-being of its residents. The IRCCS Azienda Ospedaliero-Universitaria Sant’Orsola Polyclinic is a key agent of change within this initiative. The hospital has initiated a comprehensive renovation project aligned with its commitment to the United Nations Sustainable Development Goals (SDGs), particularly SDG 3, which addresses Good Health and Well-being, and SDG 10, which addresses Reduce Inequalities. To address these goals, the hospital has engaged a research team from the University of Bologna to apply Service Design methodologies. The research aims to reshape accessibility and user experience systematically and sustainably, adhering to the principles of Design for All. The study maps diverse user groups, analyses circulation paths, and identifies physical and procedural barriers affecting vulnerable individuals, especially those with disabilities. The research introduces a novel approach by developing a comprehensive strategy rather than isolated solutions, focusing on interconnected accessibility services across pavilions. Dedicated hubs within each pavilion facilitate resource and support device exchange, improving users’ experiences. A pilot project, initially targeting wheelchair accessibility hubs, employs innovative technologies to enhance independent tool usage and monitor distribution and maintenance efficiently. The project is now entering a testing phase, during which the solution will be refined based on user feedback.