Transforming academic libraries through Internet of Things integration: Evidence from United Arab Emirates universities

BackgroundThe global increase in the Internet of Things (IoT) adoption has sparked interest in its application within the educational sector, particularly in colleges and universities. Previous studies have often focused on individual attitudes toward IoT without considering a multiperspective approach and have overlooked the impact of IoT on the technology acceptance model outside the educational domain.ObjectiveThis study aims to bridge the research gap by investigating the factors influencing IoT adoption in educational settings, thereby enhancing the understanding of collaborative learning through technology. It seeks to elucidate how IoT can facilitate learning processes and technology acceptance among college and university students in the United Arab Emirates.MethodsA questionnaire was distributed to students across various colleges and universities in the United Arab Emirates, garnering 463 participants. The data collected were analyzed using a hybrid approach that integrates structural equation modeling (SEM) and artificial neural network (ANN), along with importance-performance map analysis to evaluate the significance and performance of each factor affecting IoT adoption.ResultsThe study, involving 463 participants, identifies 2 primary levels at which factors influence the intention to adopt IoT technologies. Initial influences include technology optimism (TOP), innovation, and learning motivation, crucial for application engagement. Advanced influences stem from technology acceptance model constructs, particularly perceived ease of use (PE) and perceived usefulness (PU), which directly enhance adoption intentions. Detailed statistical analysis using partial least squares–SEM reveals significant relationships: TOP and innovativeness impact PE (β=.412, P=.04; β=.608, P=.002, respectively), and PU significantly influences TOP (β=.381, P=.04), innovativeness (β=.557, P=.003), and learning motivation (β=.752, P<.001). These results support our hypotheses (H1, H2, H3, H4, and H5). Further, the intention to use IoT is significantly affected by PE and usefulness (β=.619, P<.001; β=.598, P<.001, respectively). ANN modeling enhances these findings, showing superior predictive power (R2=89.7%) compared to partial least squares–SEM (R2=86.3%), indicating a more effective identification of nonlinear associations. Importance-performance map analysis corroborates these results, demonstrating the importance and performance of PU as most critical, followed by technology innovativeness and optimism, in shaping behavioral intentions to use IoT.ConclusionsThis research contributes methodologically by leveraging deep ANN architecture to explore nonlinear relationships among factors influencing IoT adoption in education. The study underscores the importance of both intrinsic motivational factors and perceived technological attributes in fostering IoT adoption, offering insights for educational institutions considering IoT integration into their learning environments.

Purpose- In recent years, there has been a notable surge in the utilization of emerging technologies, notably the Internet of Things (IoT), within the realm of business operations. However, empirical evidence has underscored a disconcerting trend whereby a substantial majority, surpassing 70%, of IoT adoption initiatives falter when confronted with the rigors of real-world implementation. Given the profound implications of IoT in augmenting product quality, this study endeavors to scrutinize the extant body of knowledge concerning IoT integration within the domain of agricultural logistics operations. Furthermore, it aims to discern the pivotal determinants that exert influence over the successful assimilation of IoT within business operations, with particular emphasis on logistics. Design/Methodology/Approach- The research utilizes a thorough systematic review methodology coupled with a meta-synthesis approach. In order to identify and clarify the key factors that influence IoT implementation in logistics operations, the study is grounded in the Resource-Based View theory. It employs rigorous grounded theory coding procedures, supported by the analytical capabilities of MAXQDA software. Findings- The culmination of the meta-synthesis endeavor culminates in the conceptual representation of IoT adoption within the agricultural logistics domain. This representation is underpinned by the identification of three overarching macro categories/constructs, namely: (1) IoT Technology Adoption, encompassing facets such as IoT implementation requisites, ancillary technologies essential for IoT integration, impediments encountered in IoT implementation, and the multifaceted factors that influence IoT adoption; (2) IoT-Driven Logistics Management, encompassing IoT-based warehousing practices, governance-related considerations, and the environmental parameters entailed in IoT-enabled logistics; and (3) the Prospective Gains Encompassing IoT Deployment, incorporating the financial, economic, operational, and sociocultural ramifications ensuing from IoT integration. The findings underscore the imperative of comprehensively addressing these factors for the successful assimilation of IoT within agricultural logistics processes. Originality- The originality of this research study lies in its pioneering effort to proffer a conceptual framework that furnishes a comprehensive panorama of the determinants that underpin IoT adoption, thereby ensuring its efficacious implementation within the ambit of agricultural logistics operations. Practical Implications- The developed framework, by bestowing upon stakeholders an incisive comprehension of the multifaceted factors that steer IoT adoption, holds the potential to streamline the IoT integration process. Moreover, it affords an avenue for harnessing the full spectrum of IoT-derived benefits within the intricate milieu of agricultural logistics operations.

Influence of IoT implementation on Resource management in construction

Automated inventory management systems integrated with Internet of Things (IoT) technology represent a transformative approach for Small and Medium-sized Enterprises (SMEs) in optimizing their stock levels and reducing carrying costs. A literature review also shows that there is progress in developing automated solutions, such as IoT sensors, real- time data analytics, and cloud-based applications that improve inventory control. A study shows that the adoption of IoT in automation has seen improvement in the accuracy of inventory, a reduction in stockouts, and carrying costs among SMEs. Research suggests operational improvements including reduced downtime from real time tracking, reverse logistics systems with intuitive demand forecasting for ideal stock replenishment and automation of reordering systems while effectively managing working capital. Materials and Methods: Research methodology encompassed a comprehensive analysis of peer-reviewed literature, case studies, and empirical research focusing on automated inventory management systems with IoT integration in SMEs. Criteria for choosing the literature included articles focusing on the outcomes of IoT implementation, technical integration, and performance of inventory systems. Data extraction main concern was on the efficiencies of the SC such as inventory accuracy, carrying costs, stockouts, and ROI. Descriptive methods used involved comparisons between pre-implementation and post- implementation data, use of statistical tools for measurement of performance enhancement and assessment of factors important in the deployment of the system. Results Implementation of IoT-integrated automated inventory management systems demonstrated significant improvements across multiple performance metrics. Studies reported average inventory accuracy improvements of 25-35%, reduction in carrying costs [1] by 20-30%, and decrease in stockout incidents by 35-45%. Real-time monitoring capabilities led to improved demand forecasting accuracy by 40%, while automated reordering systems reduced manual processing time by 60%. Cloud-based platforms enabled better inventory visibility and control, resulting in working capital optimization of 15-25%. SMEs implementing integrated systems reported enhanced supplier collaboration, reduced lead times, and improved customer satisfaction levels. Cost-benefit analyses indicated positive ROI within 12-18 months of system deployment. Discussion Analysis reveals several key factors contributing to successful implementation of automated inventory management systems with IoT integration. Critical success factors include proper system architecture design, effective change management strategies, and comprehensive staff training programs. Integration challenges primarily revolve around initial investment costs, technical expertise requirements, and system interoperability concerns. Studies show that the greater gains are experienced by SMEs with higher ITOR and those engaged in intricate supply chain operations. Literature review also points to differences in implementation strategies across different sectors and in their recovery, with manufacturing and retail sectors having the highest levels of adoption and improvement. Conclusion IoT-integrated automated inventory management solutions should be adopted by SMEs and are affirmed by ample data to help optimize stock status and minimize carrying costs. The tangible benefits that could be noted are accuracy in inventory, less operational costs, visibility of supply chain, and optimal use of working capital. In appointing the factors affecting the implementation success, it requires the assessment of the technical feasibility and organisational readiness as well as the management of change strategies. Research shows that dynamic technology factors will continue to improve the system’s performance and increased availability to SMEs. Due to advancement in IoT technology, artificial intelligence and cloud computing, there are potential factors that may boost the performance and cost of automatically Managed inventory systems in the future.

The burgeoning evolution of smart cities, characterized by the integration of the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning (ML), heralds a transformative era in urban management and citizen engagement. These technological advancements promise enhanced efficiency in city operations, improved public services, and a sustainable urban environment. However, the complexity and interconnectedness inherent in these systems introduce significant cybersecurity challenges, necessitating innovative approaches to safeguard the digital infrastructure of smart cities. This paper aims to explore the cybersecurity landscape of smart cities from the perspective of integrating IoT, AI, and ML for the creation of digital twins, offering a comprehensive analysis of the opportunities and threats within this domain. Smart cities leverage IoT to connect various components of the urban infrastructure, including transportation systems, utilities, and public services, creating an integrated network of devices that communicate and share data. The incorporation of AI and ML into this framework facilitates intelligent decision-making, enabling the automation of services and the optimization of resources. This synergy enhances the quality of life for residents, promotes economic development, and supports sustainable environmental practices. However, the dependence on digital technologies also exposes smart cities to a range of cybersecurity risks, from data breaches and privacy violations to the disruption of critical infrastructure. The integration of IoT, AI, and ML in smart cities, while offering unprecedented opportunities for urban innovation, also amplifies the complexity of the cybersecurity landscape. IoT devices, often designed with minimal security features, become potential entry points for cyber attacks. The vast amount of data generated and processed by these devices, if compromised, could lead to significant privacy and security breaches. AI and ML models, for their part, are susceptible to manipulation and bias, which can undermine the integrity of decision-making processes. The interconnectivity of systems means that a breach in one sector could have cascading effects throughout the city's infrastructure. Against this backdrop, the paper investigates the role of digital twins in mitigating cybersecurity risks in smart cities. Digital twins, digital replicas of physical entities or systems, offer a powerful tool for simulating and analyzing smart city operations, including cybersecurity scenarios. By mirroring the city's infrastructure in a virtual environment, digital twins allow for the identification of vulnerabilities, the simulation of cyber attacks, and the evaluation of potential impacts. This proactive approach to cybersecurity enables city administrators to anticipate threats and implement protective measures before real-world systems are compromised. The research questions guiding this inquiry include: How can the integration of IoT, AI, and ML enhance the resilience of smart cities against cyber threats? What are the specific cybersecurity challenges presented by these technologies, and how can they be addressed? And, most crucially, what role can digital twins play in fortifying the cybersecurity defenses of smart cities? To address these questions, the paper begins with a review of the current state of smart city technology, focusing on the integration of IoT, AI, and ML. It then delves into the cybersecurity challenges unique to this technological landscape, drawing on recent examples of cyber incidents in smart cities. The analysis highlights the vulnerabilities introduced by the widespread use of IoT devices and the complexities of securing AI and ML systems. Following this, the discussion turns to the potential of digital twins as a cybersecurity tool, examining how they can be employed to detect vulnerabilities, simulate attacks, and plan responses. The paper argues that while the integration of IoT, AI, and ML in smart cities presents significant cybersecurity challenges, it also offers opportunities for innovative solutions. Digital twins emerge as a promising approach to enhancing the cybersecurity posture of smart cities, enabling a dynamic and proactive defense mechanism. By facilitating the simulation of cyber threats in a controlled environment, digital twins allow city administrators to identify weaknesses, test the efficacy of protective measures, and develop more resilient urban infrastructures. In conclusion, the integration of IoT, AI, and ML in smart cities represents a double-edged sword, offering both remarkable opportunities for urban innovation and formidable cybersecurity challenges. This paper underscores the critical importance of adopting a cybersecurity perspective in the development and management of smart cities, highlighting the potential of digital twins as a strategic tool in mitigating these risks. As smart cities continue to evolve, embracing these technologies in a secure and responsible manner will be paramount in realizing their full potential while safeguarding the digital and physical well-being of urban populations.

The potential of Internet of Things technology to enhance operational efficiency and effectiveness has been recognized across various sectors. However, its adoption in Kenyan university libraries remains limited. The primary aim of this study was to examine the factors that contribute to the successful adoption of Internet of Things (IoT) technology at the Catholic University of Eastern Africa library. The ultimate goal was to identify these factors and provide recommendations for best practices in implementing IoT in the library setting. The Unified Theory of Technology Acceptance and Use served as the guiding framework. Utilizing a descriptive survey research design, this study focused on a target population of seven section head librarians and five hundred library patrons. Employing a qualitative approach, data was collected through interviews with a purposively selected university librarian, five section head librarians, and six focus group discussions (7 each), involving simple randomly sampled library patrons. Document analysis was also conducted. Content analysis and thematic categorization were used for data analysis. The study found that IoT adoption in CUEA libraries is limited by infrastructure challenges, training gaps, and organizational barriers. Robust infrastructure, user acceptance, staff training, and organizational support are key success factors for IoT adoption. The study recommends that CUEA libraries should partner with university departments to allocate resources for IoT implementation and establish training programs to enhance staff skills. The university administration should support libraries by removing organizational barriers, facilitating budgets, and creating a conducive environment for seamless IoT integration. Implementing these recommendations will enhance knowledge management capabilities and contribute to research and learning environments. This study's novelty lies in its focus on university libraries and its actionable recommendations for improving operations and services through IoT technology.

This chapter explores the integration of artificial intelligence (AI) and internet of things (IoT) technologies in autonomous systems. AI plays a crucial role in decision-making, predictive analytics, and adaptive learning, while IoT's sensor networks enable real-time data acquisition, communication, and control mechanisms. The integration of AI and IoT is explored across sectors like predictive maintenance, smart city infrastructure, healthcare, and industrial automation. However, challenges such as increasing reliance on edge computing, enhancing AI efficiency, stringent data security measures, and ethical considerations are highlighted. The chapter emphasizes the need for resilient, secure, and ethical advancements in technology to harness the potential of AI-infused autonomous systems and IoT technologies.

PurposeThis paper aims to study the antecedents of Internet of Things (IoT) adoption among farmers and determine how trust in the technology influences its adoption when mediated by perceived value and risk. Through the conceptualization of trust and perceived risk, the authors factor in farmers’ perceptions of agricultural technology providers and discuss different forms of perceived value, spanning economic, green and epistemic value.Design/methodology/approachThis paper develops a distinctive research design, drawing on elements of the value-based adoption and technology acceptance models. By linking different elements of perceived value with IoT technology, the authors also apply the service-dominant logic to this study. They study how trust affects perceived value and risk and then determine how perceived value and risk, in turn, affect IoT adoption. The authors test the hypotheses by developing a structural equation model to analyze the results of a survey, wherein 492 farmers from Iowa, the USA, participated.FindingsThe results show a positive relationship between trust and perceived value and a negative relationship between trust and perceived risk. Perceived value had a positive impact on IoT adoption, whereas perceived risk had a negative impact on IoT adoption.Practical implicationsThe research findings on trust and perceived value and risk are timely and relevant for business-to-business (B2B) marketing practitioners and agricultural stakeholders, especially in an era where farmers are expressing growing concerns about data handling risk posed by IoT technology adoption.Originality/valueThe research findings signal a transition in focus from the goods-dominant logic to the service-dominant logic in agriculture, whereby farmers are drawn to IoT technology because of perceived economic, green and epistemic value and as a result, can differentiate themselves on how well they deploy operant resources. This paper not only provides a unique conceptualization of perceived value but also pave the way for a richer conceptualization of IoT core functions that enable farmers to fulfill green and epistemic goals. This is the first B2B marketing paper discussing the antecedents of IoT adoption in agriculture, such as farmers’ perceptions of both monetary and non-monetary forms of value and perceived data handling risk.

The integration of Internet of Things (IoT) technologies in academic libraries has the potential to revolutionize service delivery, resource management, and user experiences. This study investigated the adoption and integration of IoT in academic libraries across federal tertiary institutions in Kano State, Nigeria. Employing a cross-sectional survey design, quantitative data were collected from 167 librarians using a structured questionnaire. The revealed high awareness of IoT technologies among librarians, with a mean IoT awareness score of 4.6 on a Likert scale. However, actual adoption levels remain low due to challenges such as limited funding, inadequate infrastructure, and insufficient technical expertise. A strong positive correlation (r = 0.96, p &lt; 0.001) between years of professional experience and IoT usage levels underscores the importance of experienced staff in leveraging IoT effectively. The study concluded that while academic libraries in Kano State demonstrate readiness and a positive attitude findings toward IoT, significant barriers must be addressed to realize its full potential. Recommendations include targeted capacity-building programs, strategic investment in infrastructure, and the development of clear IoT adoption policies. These findings offer practical insights for policymakers, library administrators, and stakeholders to facilitate successful IoT implementation in Nigerian academic libraries.

"How can the integration of Internet of Things (IoT) technology enhance the sustainability and efficiency of green building (G.B.) design?" is the central research question that this study attempts to answer. This investigation is important because it examines how green building and IoT technology can work together. It also provides important information about how to use contemporary technologies for environmental sustainability in the building sector. The paper examines a range of IoT applications in green buildings, focusing on this intersection. These applications include energy monitoring, occupant engagement, smart building automation, predictive maintenance, renewable energy integration, and data analytics for energy efficiency enhancements. The objective is to create a thorough and sustainable model for designing green building spaces that successfully incorporates IoT, offering industry professionals cutting-edge solutions and practical advice. The study uses a mixed-methods approach, integrating quantitative data analysis with qualitative case studies and literature reviews. It evaluates how IoT can improve energy management, indoor environmental quality, and resource optimization in diverse geographic contexts. The findings show that there has been a noticeable improvement in waste reduction, energy and water efficiency, and the upkeep of high-quality indoor environments after IoT integration. This study fills a major gap in the literature by offering a comprehensive model for IoT integration in green building design, which indicates its impact. This model positions IoT as a critical element in advancing sustainable urban development and offers a ground-breaking framework for the practical application of IoT in sustainable building practices. It also emphasizes the need for customized IoT solutions in green buildings. The paper identifies future research directions, including the investigation of advanced IoT applications in renewable energy and the evaluation of IoT's impact on occupant behavior and well-being, along with addressing cybersecurity concerns. It acknowledges the challenges associated with IoT implementation, such as the initial costs and specialized skills needed.

PurposeThe need to improve sustainable construction with the appropriate technology adoption in the fourth and fifth industrial revolutions cannot be overemphasized. This study modelled the adoption of Internet of things (IoT) technologies in the construction industry to improve sustainable construction. Consequently, the study would assist construction stakeholders and policymakers in achieving sustainable construction through concerted efforts toward improving IoT adoption.Design/methodology/approachThe study obtained the IoT technologies and the challenges of IoT adoption in the construction industry through a literature review. Subsequently, the awareness (knowledge of the existence and uses) of IoT technologies, the significance of the challenges and the level of adoption of the IoT technologies were tested on construction stakeholders in Kigali with a structured questionnaire. Consequently, a structural equation model of IoT adoption was developed.FindingsThe structural equation model indicates the relationship between the awareness, challenges and adoption of IoT technologies. It equally describes the effect sizes of the awareness and challenges of IoT on the adoption of IoT technologies.Research limitations/implicationsThis study is beneficial to construction stakeholders as it portrays the exclusive impacts of the awareness and the challenges of IoT technologies on the adoption of IoT. The study also benefits the government and policymakers as it provides a basis for intensifying efforts to create awareness and mitigate the challenges of IoT adoption for sustainable construction. The study also provides a basis for future studies on IoT adoption in the construction industry.Originality/valueThere are several studies on the adoption of IoT. There is however scarcity of studies on how the awareness and the challenges of IoT technologies impact the adoption of IoT in the construction industry. Thus, this study bridges the gap by modelling the adoption of IoT technologies for improved sustainable construction.

Internet of Things (IoT) technology is something that is equipped with sensors and software so that it can send data over a network without human interaction. As a result, the Internet of Things can improve connectivity by connecting many devices via the internet, facilitating human interaction with machines. This research was conducted with the aim of increasing efficiency, reliability and innovation in the teaching and learning process. By using IoT, this research focuses on developing interactive and personalized learning media to increase students' understanding of technology. In addition, this research aims to improve teachers' abilities in using information technology to help students learn to use it. In conducting this research, researchers used quantitative methods in carrying out the research. The data obtained by the researcher was obtained through distributing questionnaires presented by the researcher via a goggle from application. The distribution of this questionnaire is carried out by researchers online, and then the results of the distribution of this questionnaire will be processed using an SPSS application. From this research, researchers can conclude that the integration of Internet of Things (IoT) technology can increase classroom management efficiency. With the help of the Internet of Things (IoT), teachers can monitor and manage classes more efficiently and intelligently by collecting data such as student activity, room temperature, and other information. Thus, IoT allows teachers to make smarter and strategic decisions about classroom management. Based on the results of this research, the impact of integrating IoT technology can provide benefits for teachers and students. Developing digital skills is one of the benefits of integrating IoT technology. By learning how to use Internet of Things technology in learning, teachers can improve their digital skills and increase their ability to use technology to improve the efficiency and quality of education.

The rise of the Internet of Things (IoT) has transformed manufacturing and supply chain management. This article examines how IoT integration in lean manufacturing significantly enhances real-time supply chain optimization. Lean manufacturing aims to reduce waste and increase efficiency, making it a perfect match for IoT technology, which connects devices and systems for real-time data collection and analysis. The paper explores various applications of IoT in lean manufacturing, such as predictive maintenance, real-time inventory management, quality control, energy efficiency, sensor technology, data analytics, and cloud computing, it further elucidates how manufacturers can achieve enhanced supply chain visibility, reduced waste, improved quality, and increased agility. Predictive maintenance uses IoT sensors to monitor equipment, allowing maintenance to be performed only when necessary, reducing downtime and extending equipment life. Real-time inventory management tracks stock levels and movements with IoT sensors and RFID tags, ensuring optimal inventory levels and reducing excess stock. IoT also enhances quality control by detecting defects in real-time and enabling immediate corrective actions. Energy efficiency is improved through IoT technology that monitors and optimizes energy usage, reducing costs and environmental impact. Additionally, IoT provides end-to-end visibility and transparency across the supply chain, facilitating better decision-making and coordination. The article includes detailed analysis and case studies demonstrating how IoT-driven innovations lead to improved operational efficiency, cost reduction, and better overall supply chain performance. It also addresses the challenges and ethical considerations of IoT implementation, such as data security, privacy concerns, and the potential impact on the workforce. Finally, the article offers insights into future trends and advancements in IoT technology, highlighting its potential to further revolutionize lean manufacturing and supply chain management. By embracing IoT, companies can not only streamline their operations but also gain a competitive edge in a rapidly evolving marketplace. The integration of IoT with lean principles allows for more adaptive and resilient supply chains, which are crucial in today’s dynamic business environment. As technology continues to advance, the opportunities for IoT to drive innovation and efficiency in manufacturing and supply chains will only grow, making it a key area of focus for future research and development.

PurposeFor the provision of smart library services to end users, tools of the Internet of Things (IoT) play a significant role. The study aims to discover the factors influencing the adoption of IoT in university libraries, investigate the impact of IoT on university library services and identify challenges to adopt IoT applications in university libraries.Design/methodology/approachA systematic literature review was carried out to address the objectives of the study. The 40 most relevant research papers published in the world’s leading digital databases were selected to conduct the study.FindingsThe findings illustrated that rapid growth in technology, perceived benefits, the networked world and the changing landscape of librarianship positively influenced the adoption of IoT in university libraries. The study also displayed that IoT supported library professionals to initiate smart library services, assisted in service efficiency, offered context-based library services, provided tracking facilities and delivered effective management of library systems. Results also revealed that a lack of technical infrastructure, security and privacy concerns, a lack of technological skills and unavailability of policy and strategic planning caused barriers to the successful adoption of IoT applications in university libraries.Originality/valueThe study has provided theoretical implications through a valuable addition to the current literature. It has also offered managerial implications for policymakers to construct productive policies for the implementation of IoT applications in university libraries for the attainment of fruitful outcomes. Finally, the study provides a baseline for understanding the adoption of IoT in academic libraries.

The rapid development of technology is bringing about fundamental changes in all areas of life, transforming traditional methods into digital solutions. In recent years, technological advancements have offered new opportunities across various sectors—from production and logistics to healthcare and agriculture—delivering significant gains in terms of efficiency and sustainability. In this context, Internet of Things (IoT) technologies are being used in the agricultural sector to increase productivity, optimize resource utilization, and promote sustainable production processes. Thanks to this technology, farmers can monitor environmental factors such as soil moisture, temperature, light, and pH levels in real time, and increase yield by applying appropriate agricultural techniques. Despite all these advantages, some farmers may be reluctant to adopt IoT due to concerns over its complexity compared to traditional methods or the perceived risk of job loss. This study aims to evaluate farmers’ attitudes toward IoT technology by taking their concerns into account. The study analyzes whether three different factors have a positive (plus sign) or negative (minus sign) effect on IoT adoption in the agricultural sector. The analysis reveals not only significant differences but also similarities among different farmer groups. These findings provide important insights into which factors are more influential in the adoption of IoT. It is expected that such analyses will help guide the development of strategies tailored to different groups and support the wider adoption of IoT technologies in agriculture.