Search Results (188)

This paper introduces an innovative open-source hardware platform designed for multi-sensor environmental monitoring, rooted in the outcomes of the “Smart Water” project. The primary objective of this platform is to facilitate advanced PCB design education by offering students a modular, expandable, and feature-rich embedded hardware environment. The platform serves as a practical training ground, enabling students to experiment with diverse sensing techniques and refine their skills in the intricacies of PCB design. The “Smart Water” project, which forms the foundation of this educational platform, has yielded invaluable insights into environmental monitoring technologies. Leveraging these findings, our hardware platform integrates a variety of sensors capable of measuring crucial environmental parameters such as water quality, temperature, and atmospheric conditions. The modular design allows students to explore various sensor combinations and experiment with custom configurations, fostering a deeper understanding of sensor integration and optimization. Key features of the platform include its expandability, encouraging students to develop add-on modules for specific applications or to enhance existing functionalities. This approach not only promotes creativity but also instills a sense of ownership and collaboration among students, as they contribute to the continual evolution of the hardware platform. The feature-rich nature of the embedded system enables comprehensive experimentation in sensor data acquisition, processing, and communication, providing a holistic learning experience. Full article

As a key piece of equipment in badminton, the surface treatment technology of rackets has garnered significant attention in the fields of material science and sports engineering. This study is the first to systematically review research on racket coatings, integrating interdisciplinary knowledge on the classification of functional coatings, their performance-enhancing principles, and their relationship with competitive levels, thereby addressing a gap in theoretical research in this field. This study focuses on four major functional coating systems: superhydrophobic coatings (to improve environmental adaptability and reduce air resistance), anti-scratch coatings (to prolong the life of the equipment), vibration-damping coatings (to optimise vibration damping performance), and strength-enhancing coatings (to safeguard structural stability). In badminton, differences in player skill levels and usage scenarios lead to variations in racket materials, which, in turn, result in different preparation processes and performance effects. The use of vibration-damping materials alleviates the impact force on the wrist, effectively preventing sports injuries caused by prolonged training; leveraging the aerodynamic properties of superhydrophobic technology enhances racket swing speed, thereby improving hitting power and accuracy. From the perspective of performance optimization, coating technology improves athletic performance in three ways: nanocomposite coatings enhance the fatigue resistance of the racket frame; customized damping layers reduce muscle activation delays; and surface energy regulation technology improves grip stability. Challenges remain in the industrial application of environmentally friendly water-based coatings and the evaluation system for coating lifespan under multi-field coupling conditions. Future research should integrate intelligent algorithms to construct a tripartite optimization system of “racket-coating-user” and utilize digital sports platforms to analyze its mechanism of influence on professional athletes’ tactical choices, providing a theoretical paradigm and technical roadmap for the targeted development of next-generation smart badminton rackets. Full article

The hospitality sector is undergoing a rapid digital change due to smart technology and artificial intelligence. This presents both possibilities and problems for the development of sustainable innovation. Yet, little is known about how leaders’ technological competencies affect employees’ capacity to engage in environmentally responsible innovation. This study addresses this gap by examining how leaders’ competencies in smart technology, artificial intelligence, robotics, and algorithms (STARA) shape employees’ green innovative behavior in hotels. Anchored in person–job fit theory and cognitive appraisal theory, we propose that when employees perceive a strong alignment between their skills and the technological demands introduced by STARA, they are more likely to appraise such technologies as opportunities (challenge appraisals) rather than threats (hindrance appraisals). These appraisals, in turn, mediate the link between leadership and green innovation. Convenience sampling was used to gather data from staff members at five-star, ecologically certified hotels in Sharm El-Sheikh, Egypt. According to structural equation modeling using SmartPLS, employees’ green innovation behaviors are improved by leaders’ STARA abilities. Crucially, staff members who viewed STARA technologies as challenges (i.e., chances for learning and development) converted leadership skills into more robust green innovation results. Conversely, employees who perceived these technologies as obstacles, such as burdens or threats, diminished this beneficial effect and decreased their desire to participate in green innovation. These findings highlight that the way employees cognitively evaluate technological change determines whether leadership efforts foster or obstruct sustainable innovation in hotels. Full article

This article deals with the analysis and exploration of the concept of integrating human knowledge (HK) and artificial intelligence (AI) in the management process. The authors point out that the implementation of advanced AI technologies into already functioning and often complex systems, such as enterprise resource planning (ERP), presents significant technical challenges and requires a well-thought-out integration strategy. The complexity arises from the need to align new solutions with existing processes, resources, and data. Using the example of a fuel distribution system, the authors present the concept of integrating human knowledge (HK) and artificial intelligence (AI) in the management process. The article presents a comprehensive analysis of the smart upgrade of fuel delivery management (FDM) architecture by incorporating an AI app to solve complex problems, such as predicting demand or traffic flows, as well as correctly detecting near-miss events. Technological convergence enables the mutual pursuit of improving the management process by developing soft skills and expanding knowledge managers. The authors’ findings show that an important factor for successful convergence is horizontal and vertical matching of the human knowledge and artificial intelligence cooperation for archive max positive synergy. Some recommendations could be useful for tank truck operators as a starting point to predict demand patterns, smart route planning, etc., where an AI app could be very successful. Full article

Sustainable digital transformation in healthcare is becoming increasingly urgent; there is limited empirical research on the organizational factors that contribute to success in emerging economies. This study addresses this gap by analyzing how leadership, knowledge management, and technology acceptance influence the development of smart hospitals, using Thailand as a case study. A mixed-methods approach was adopted, combining semi-structured interviews with senior administrators and a survey involving 370 respondents from 37 hospitals. The data were analyzed using exploratory factor analysis and multiple regression. The results indicate that institutional knowledge repositories and leaders’ reading comprehension skills significantly enhance the digital maturity of hospitals. Conversely, reliance on traditional communication methods and an excessive focus on ease of use negatively impact outcomes. These findings suggest that leadership-driven cognitive readiness and well-structured knowledge systems are more important than merely simplifying digital solutions. The originality of this research lies in integrating sustainability principles into digital transformation, connecting management competencies with the resilience of health systems. This study offers actionable insights for policymakers in low- and middle-income countries and presents a framework for the sustainable development of smart hospitals. Limitations and suggestions for future research are also discussed. Full article

This study evaluates the degree to which small and medium sized enterprises (SMEs) are prepared to adopt smart manufacturing in contrast to large enterprises, a transition that depends on the effective use of the Internet of Things, artificial intelligence (AI), and advanced analytics. While many large multinational companies have already integrated such technologies, smaller firms still struggle because of tight budgets, limited technical expertise, and difficulties in scaling new systems. To capture these realities, the investigation refines the Initiative Mittelstand-Digital für Produktionsunternehmen und Logistik-Systeme (IMPULS) Industry 4.0 readiness model, which was initially developed to help German SMEs, so that it aligns with the circumstances faced by smaller manufacturers. A thorough review of published work first surveys existing readiness and maturity frameworks, highlights their limitations, and guides the selection of new, SME-specific indicators. The framework gauges readiness across six dimensions: strategic planning and organizational design, smart factory infrastructure, lean operations, digital products, data-driven services, and workforce capability. Each dimension is operationalized through a questionnaire that offers clear benchmarks and actionable targets suited to the current resources of each enterprise. Weaving strategic vision, skill growth, and cooperative support, the approach offers managers a direct path to sharper competitiveness and lasting innovation within a changing industrial landscape. Additionally, a separate Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis is provided for each dimension based on survey data offering decision-makers concise guidance for future investment. The proposed adaptation of the IMPULS framework, validated through empirical data from 31 SMEs, introduces a novel readiness index, diagnostic gap metrics, and actionable cluster profiles tailored to developing-country industrial ecosystems. Full article

The rapid development of smart home and building technologies requires educational methods that facilitate the integration of theoretical knowledge with practical, system-level design skills. Computer-assisted tools play a crucial role in this process by enabling students to experiment with complex Internet of Things (IoT) and building automation ecosystems in a risk-free, iterative environment. This paper proposes a pedagogical framework that integrates simulation-based prototyping with collaborative and spatial design tools, supported by elements of design thinking and blended learning. The approach was implemented in a master’s-level Smart Building Systems course, to engage students in interdisciplinary projects where virtual modeling, digital collaboration, and contextualized spatial design were combined to develop user-oriented smart space concepts. Analysis of project outcomes and student feedback indicated that the use of simulation and visualization platforms may enhance technical competencies, creativity, and engagement. The proposed framework contributes to engineering education by demonstrating how computer-assisted environments can effectively support practice-oriented, user-centered learning. Its modular and scalable structure makes it applicable across IoT- and automation-focused curricula, aligning academic training with the hybrid workflows of contemporary engineering practice. Concurrently, areas for enhancement and modification were identified to optimize support for group and creative student work. Full article

Green and digital transitions represent a dual strategic objective for the European Union (EU), requiring behavioral changes from citizens, markets, and state institutions. To support these transformations, the EU has developed an extensive policy framework that is backed by significant financial instruments. However, the existing research suggests that these transitions may exacerbate both spatial and socioeconomic inequalities, depending on country-specific conditions and institutional capacities. This paper investigates how environmental and technological contexts, alongside EU-transition-related policies, influence regional and income inequalities within the selected EU countries. Using panel data covering the period 2007–2020 and employing a Generalized Least Squares (GLS) estimator, the present study reveals the complex relationship between structural conditions, policy designs, and inequality outcomes. The results show that smart and green policies tend to mitigate spatial inequalities, though they are found to be less effective in addressing income inequalities. By contrast, the contextual dynamics of the twin transition, such as skill intensity, digital adoption, and emissions, exhibit mixed effects, sometimes reinforcing inequality. The findings underline the urgency of designing inclusive EU policies that combine green and smart transition measures while accounting for country- and region-specific challenges. Such an integrated approach is essential for ensuring that the twin transition strengthens social cohesion in Europe, rather than undermining it. Full article

Sierra Leone possesses distinct educational, economic, and social characteristics. Public universities in the country, funded by the government, are mandated to promote sustainable development, ethical conduct, and social welfare, aligning with national development strategies such as the Midterm National Development Plan and the Education Sector Plan, which emphasize leadership, diversity, and ethical standards to advance sustainable development practices. This study applies Transformational Leadership Theory to investigate the influence of transformational leadership on corporate social responsibility, exploring the mediating role of innovative work behavior and the moderating effect of organizational culture on this relationship. Using a stratified sampling technique, data were collected from 367 employees across six public universities in Sierra Leone and analyzed with SMART PLS software 4.1.1.2. The findings revealed that transformational leadership positively and significantly impacts corporate social responsibility and innovative work behavior, with innovative work behavior partially mediating the relationship between transformational leadership and corporate social responsibility, while organizational culture positively and significantly moderates this relationship. Based on these findings, the study recommends that public universities in Sierra Leone integrate transformational leadership principles into their institutional frameworks to improve organizational outcomes and leadership effectiveness. This can be achieved through leadership development programs emphasizing transformational attributes such as inspirational motivation, individualized consideration, and vision-sharing, alongside mentorship programs for leaders at all levels to strengthen leadership skills and foster an organizational culture aligned with institutional goals. Full article

Artificial intelligence (AI) soft skills have become increasingly vital in today’s technology-driven world, as they support decision-making systems, strengthen collaboration among stakeholders, and enable individuals to adapt to rapidly changing environments—factors that are fundamental for achieving the sustainability goals of smart cities. Even though AI soft skills are becoming more important, no scale specifically designed to identify and evaluate individuals’ AI soft skills has been found in the existing literature. Therefore, this paper aimed to develop a reliable and valid scale to identify the AI soft skills of individuals. A sample of 685 individuals who were employed in AI-active sectors, with a minimum of a bachelor’s degree, and at least one year of AI-related work experience, participated in the study. A sequential exploratory mixed-methods research design was utilized. Exploratory factor analysis (EFA) identified a five-factor structure that accounted for 67.37% of the total variation, including persuasion, collaboration, adaptability, emotional intelligence, and creativity. Factor loadings ranged from 0.621 to 0.893, and communalities ranged from 0.587 to 0.875. Confirmatory factor analysis (CFA) supported this structure, with strong model fit indices (GFI = 0.940, AGFI = 0.947, NFI = 0.949, PNFI = 0.833, PGFI = 0.823, TLI = 0.972, IFI = 0.975, CFI = 0.975, RMSEA = 0.052, SRMR = 0.035). Internal consistency for each factor was high, with Cronbach’s alpha values of dimensions ranging from 0.804 to 0.875, with a value of 0.921 for the overall scale. Convergent and discriminant validity analyses further confirmed the construct’s robustness. The finalized AI soft skills (AISS) scale, consisting of 24 items, offers a psychometrically valid and reliable tool for assessing essential AI soft skills in professional contexts. Ultimately, this developed scale enables the determination of the social and cognitive skills needed in the human-centered and participatory governance structures of smart cities, supporting the achievement of specific Sustainable Development Goals such as SDG 4, SDG 8, and SDG 11, and contributes to the design of policies and training programs to eliminate the deficiencies of individuals in these areas. Thus, it becomes possible to create qualified human resources that support sustainable development in smart cities, and for these individuals to take an active part in the labor market. Full article

This study explores the migration intentions of university students—representing the potential creative class—in Erzurum, a medium-sized city in eastern Turkey experiencing shrinkage. Within the theoretical framework of shrinking cities, it investigates how economic, social, physical, and personal factors influence students’ post-graduation stay or leave decisions. Survey data from 742 Architecture and Fine Arts students at Atatürk University were analyzed using factor analysis, logistic regression, and correlation to identify key migration drivers. Findings reveal that, in addition to economic concerns such as limited job opportunities and low income, personal development opportunities and social engagement also play a decisive role. In particular, the perception of limited chances for skill enhancement and the belief that Erzurum is not a good place to meet people emerged as the strongest predictors of migration intentions. These results suggest that members of the creative class are influenced not only by economic incentives but also by broader urban experiences related to self-growth and social connectivity. This study highlights spatial inequalities in access to cultural, educational, and social infrastructure, raising important questions about spatial justice in shrinking urban contexts. This paper contributes to the literature on shrinking cities by highlighting creative youth in mid-sized Global South cities. It suggests smart shrinkage strategies focused on creative sector development, improved quality of life, and inclusive planning to retain young talent and support sustainable urban revitalization. Full article

Background: Family caregivers are a vital yet often under-recognized part of the healthcare system. They provide essential emotional, physical, and logistical support to individuals with illness, disability, or frailty, and their contributions improve continuity of care and reduce system strain. However, many healthcare and social service providers are not equipped to meaningfully engage caregivers as partners. In Alberta, stakeholders validated the Caregiver-Centered Care Competency Framework and identified the need for a three-tiered education model—Foundational, Advanced, and Champion—to help providers recognize, include, and support family caregivers across care settings. This paper focuses on the development and early evaluation of the Advanced Caregiver-Centered Care Education modules, designed to enhance the knowledge and skills of providers with more experience working with family caregivers. The modules emphasize how partnering with caregivers benefits not only the person receiving care but also improves provider effectiveness and supports better system outcomes. Methods: The modules were co-designed with a 154-member interdisciplinary team and grounded in the competency framework. Evaluation used the first three levels of the Kirkpatrick–Barr health workforce education model. We analyzed pre- and post-surveys from the first 50 learners in each module using paired t-tests and examined qualitative feedback and SMART goals through inductive content analysis. Results: Learners reported a high level of satisfaction with the education delivery and the knowledge and skill acquisition. Statistically significant improvements were observed in 53 of 54 pre-post items. SMART goals reflected intended practice changes across all six competency domains, indicating learners saw value in engaging caregivers as partners. Conclusions: The Advanced Caregiver-Centered Care education improved providers’ confidence, knowledge, and skills to work in partnership with family caregivers. Future research will explore whether these improvements translate into real-world practice changes and better caregiver experiences in care planning, communication, and navigation. Full article

This study conducts a comprehensive systematic review of the economic impact of Digital Twin (DT) technology within the Architecture, Engineering, and Construction (AEC) industry, following the PRISMA methodology. While DT adoption has been accelerated by advancements in Building Information Modelling (BIM), the Internet of Things (IoT), and data analytics, significant challenges persist—most notably, high initial investment costs and integration complexities. Synthesising the literature from 2016 onwards, this review identifies sector-specific barriers, regulatory burdens, and a lack of standardisation as key factors constituting DT implementation costs. Despite these hurdles, DTs demonstrate strong potential for enhancing construction productivity, optimising lifecycle asset management, and enabling predictive maintenance, ultimately reducing operational expenditures and improving long-term financial performance. Case studies reveal cost efficiencies achieved through DTs in modular construction, energy optimisation, and infrastructure management. However, limited financial resources and digital skills continue to constrain the uptake across the sector, with various extents of impact. This paper calls for the development of unified standards, innovative public–private funding mechanisms, and strategic collaborations to unlock and utilise DTs’ full economic value. It also recommends that future research explore theoretical frameworks addressing governance, data infrastructure, and digital equity—particularly through conceptualising DT-related data as public assets or collective goods in the context of smart cities and networked infrastructure systems. Full article

Workforce transformation is one of the most pressing challenges in the AI-driven construction industry, as traditional skilled labour roles are rapidly evolving into more interdisciplinary, digitally enabled positions. This study aims to investigate how AI is fundamentally reshaping skill requirements within the construction sector, to analyse stakeholder perceptions and adaptive responses to workforce transformation, and to explore strategies for optimizing construction workforce development to facilitate the critical transition from traditional “skilled workers” to contemporary “smart talent.” It employs phenomenological qualitative research methodology to conduct in-depth interviews with 20 stakeholders in Chongqing, and uses NVivo 14 to conduct thematic analysis of the data. The findings indicate that AI has penetrated all areas of the construction process and is transforming jobs to more likely be digitalized, collaborative, and multi-faceted. However, significant cognitive disparities and varying adaptive capacities among different stakeholder groups have created structural imbalances within the workforce development ecosystem. Based on these key findings, a four-pillar talent development strategy is proposed, encompassing institutional support, educational reform, enterprise engagement, and group development, while stressing the necessity for systemic-orchestrated coordination to reimagine a smart talent ecosystem. This study advances theoretical understanding of digital transformation within construction labour markets, while offering real pathways and institutional contexts for developing regions that desire to pursue workforce transformation and sustainable industrial development in the AI era. Full article

Background: Minimally invasive surgery (MIS) is increasingly adopted in pediatric surgical practice, yet it demands specific technical skills that require structured training. Simulation-based education offers a safe and effective environment for skill acquisition, especially in complex procedures such as thoracoscopic repair of esophageal atresia with tracheoesophageal fistula (EA-TEF). Objective: This study aimed to evaluate the effectiveness of a 3D-printed simulator for training pediatric surgeons in thoracoscopic EA-TEF repair, assessing improvements in operative time and technical performance. Methods: A high-fidelity, 3D-printed simulator replicating neonatal thoracic anatomy was developed. Six pediatric surgeons at different training levels performed eight simulation sessions, including fistula ligation and esophageal anastomosis. Operative time and technical skill were assessed using the Stanford Microsurgery and Resident Training (SMaRT) Scale. Results: All participants showed significant improvements. The average operative time decreased from 115.6 ± 3.51 to 90 ± 6.55 min for junior trainees and from 100.5 ± 3.55 to 77.5 ± 4.94 min for senior trainees. The mean SMaRT score increased from 23.8 ± 3.18 to 38.3 ± 3.93. These results demonstrate a clear learning curve and enhanced technical performance after repeated sessions. Conclusions: Such 3D-printed simulation models represent an effective tool for pediatric MIS training. Even within a short time frame, repeated practice significantly improves surgical proficiency, supporting their integration into pediatric surgical curricula as an ethical, safe, and efficient educational strategy. Full article