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The Internet of Things has made the shift to the digital era possible, even though the Architecture, Engineering and Construction (AEC) sector has not embraced nor integrated it within the core functions compared to other sectors. The need to enhance sustainable construction with the adoption of Internet of Things in this sector cannot be overemphasized. However, the real-world applications of Internet of Things in smart buildings remain relatively unexplored in the AEC sector due to several issues related to deployment and energy-saving potentials. Given these challenges, this paper proposes to identify the present state of development and research in Internet of Things and smart buildings, identify Internet of Things clusters and applications in smart buildings.

Bibliometric analyses of papers from 2010 to 2023 using the Scopus database and scientometric evaluations using the VosViewer software were undertaken. The proper search keyword was identified by using the phrases “ Internet of Things” and “Smart Building”. A total of 1158 documents in all, written by 3540 different writers, representing 2285 different institutions from 97 different countries were looked at. A metasynthesis was conducted and a system of Internet of Things applications in a smart building is illustrated.

The development of IoT and Smart Buildings is done in two phases: initiation (2010–2012) and development phase (2013–2023). The IoT clusters comprised Internet of things, energy efficiency, intelligent buildings, smart buildings and automation; while the most commonly used applications were analysed and established. The study also determined the productive journals, documents, authors and countries.

Documents published in the Scopus database from 2010 to 2023 were considered for the bibliometric analysis. Journal articles, conference papers, reviews, books and book chapters written in English language represent the inclusion criteria, while articles in press, conference reviews, letters, editorials, undefined sources and all medical and health publications were excluded.

The results of this study will be used by construction stakeholders and policymakers to identify key themes and applications in IoT-enabled smart buildings and to guide future research in the policymaking process of asset management.

The study utilised bibliometric analysis, scientometrics and metasynthesis to investigate Internet of things applications in smart buildings. The study identified Internet of things clusters and applications for smart building design and construction.

This research focuses on the challenges of establishing a better medical system that can detect and diagnose diseases earlier. Using such cutting-edge health systems, healthcare practitioners may quickly and effectively manage patients’ medical issues by providing the appropriate data at the right time about the right people. The advancement of technology has increased the usefulness of devices that routinely analyse health measurements or monitoring time-sensitive health-related data. Medical professionals and patients alike are downloading health-related mobile apps to better track and manage their health. The research evidences how Internet of Things (IoT) technology may be used to support health care.

The primary aim of this study is to examine the decision-making process of a reverse supply chain within a cooperative-competitive environment, with a particular emphasis on the incorporation of Internet of Things (IoT) technology in the recycling process.

The impact of IoT on recycling effectiveness, RF (refurbished) product demand and remanufacturing expenses is analyzed. The game-theoretic models are constructed to incorporate the co-competitive relationship between a IR (Internet Recycler) and a remanufacturer, with specific attention paid to the IR's application of IoT technology.

The results indicate that the use of IoT reduces the costs associated with remanufacturing, leading to an increase in the transfer price of pre-owned items procured from IRs. The efficacy of the reverse supply chain depends not only on its cost-saving capabilities but also on consumer preferences toward RF and remanufactured (RM) items.

IoT technology can benefit Internet recycling and remanufacturing by enhancing transparency, quality monitoring and automation of processes. It can also help reduce operating costs, improve customer engagement and incentivize cooperation between organizations.

This study examined the strategic decision-making processes in the context of cooperation and competition between IR and remanufacturers. In addition, this research makes a valuable contribution to the literature by elucidating the optimal conditions for the effective implementation of Internet of Things (IoT) technology in recycling operations.

The Internet of Things (IoT) is perceived as an evolving trend in the tourism industry, with the potential to change its dynamics. IoT will help destinations, airlines, hotels and cruises personalise their services for tourists and guests. Moreover, it has several advantages for them, such as cost savings, increased productivity, greater efficiency and customised and differentiated services. The readers of this chapter will learn about the trends of IoT in the tourism industry, discover its benefits and learn about the most critical applications.

The current study aimed to identify the impact of the dynamic capabilities on the circular economy in Jordan's small- and medium-sized manufacturing enterprises sector as and the mediating role of industrial Internet of things.

This study surveyed small and medium manufacturing enterprises operating in Jordan and collected 459 responses through an online self-administered questionnaire. The effects of dynamic capabilities and the industrial Internet of things on the circular economy were analyzed using covariance-based structural equation modeling (CB-SEM).

Empirical results showed that all hypotheses are accepted. The results also revealed that the relationship between dynamic capabilities (sensing, seizing and reconfiguring) on a circular economy is mediated by the industrial Internet of things.

This work expanded the application of the dynamic capabilities view to investigate the antecedent effects of the industrial Internet of things and the circular economy and deepened understanding of the dynamic capabilities view theory in assessing the dynamic activities of these firms based on the three dimensions of sensing, seizing and reconfiguring. In general, this study made a theoretical and managerial contribution to supply chain and circular economy literature.

The purpose of this study is to determine the characteristics of the studies in terms of country, participant profile and methodology, as well as to determine what the Internet of Things (IoT) is currently contributing to higher education.

The study was developed following the methodology supported by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement and the PICOS strategy, retrieving scientific literature from Web of Science, Scopus, ERIC and Google Scholar. Of the 237 studies that the search yielded, 11 were included.

The results showed that among the opportunities offered by IoT is that it not only brings the introduction of information and communication technology into the classroom, but also enhances student interest, thus, improving the quality of teaching in higher education. On the other hand, one of the challenges it faces is the attitude of teachers towards its adoption, as well as the level of digital competence of teachers.

This study presents how higher education institutions are including the IoT in their educational activities. The IoT refers to a network of digital interconnectivity between devices, people and the internet itself that enables the exchange of data between them, allowing key information about the use and performance of devices and objects to be captured to detect patterns, make recommendations, improve efficiency and create better user experiences.

In this chapter, we investigate the role of the Internet of Things (IoT) for a more sustainable future. The IoT is an umbrella term that refers to an interrelated network of devices connected to the internet. It also encompasses the technology that enables communication between these devices as well as between the devices and the cloud. The emergence of low-cost microprocessors, sensors and actuators, as well as access to high bandwidth internet connectivity, has led to the massive adoption of IoT systems in everyday life. IoT systems include connected vehicles, connected homes, smart cities, smart buildings, precision agriculture, among others. During the last decade, they have been impacting human activities in an unprecedented way. In essence, IoT technology contributes to the improvement of citizens' quality of life and companies' competitiveness. In doing so, IoT is also contributing to achieve the Sustainable Development Goals (SDGs) that were adopted by the United Nations in 2015 as an urgent call to action by all countries to eradicate poverty, tackle climate change and ensure that no one is left behind by 2030. The World Economic Forum (WEF) recognises that IoT is undeniably one of the major facilitators for responsible digital transformation, and one of its reports revealed that 84% of IoT deployments are presently addressing, or can potentially address the SDGs. IoT is closely interlinked with other emerging technologies such as Artificial Intelligence (AI) and Cloud Computing, for the delivery of enhanced and value-added services. In recent years, there has been a push from the IoT research and industry community together with international stakeholders, for supporting the deployment and adoption of IoT and AI technologies to overcome some of the major challenges facing mankind in terms of protecting the environment, fostering sustainable development, improving safety and enhancing the agriculture supply chain, among others.

The purpose of this study is to analyze the technological change under development linked to the convergence of the Internet of Things (IoT) and digital transformation (DT) from the perspective of a scientific mapping in a context marked by the occurrence of an unexpected event that accelerated this process such as the SARS-CoV-2 pandemic and its variants.

The study was developed under the longitudinal scientific mapping approach and considered the period 1990–2021 using as a basis the descriptors DT and IoT. The steps followed were identification and selection of keywords; design and application of an algorithm to identify these selected keywords in titles, abstracts and keywords using terms in Web of Science (WoS) to contrast them; and performing a data processing based on the journals in the Journal Citation Report during 2022. The longitudinal study uses scientific mapping to analyze the evolution of the scientific literature that seeks to understand the acceleration in the integration of technology and its impact on the human factor, processes and organizational culture.

This study showed that the technologies converging around IoT form the basis of the main DT processes being experienced on a global scale; furthermore, it was shown that the pandemic accelerated the convergence and application of new technologies to support the major changes required for a world with new needs. Finally, China and the USA differ significantly in the production of scientific knowledge with respect to the first eight followers.

The knowledge gap addressed by this study is to identify the production of scientific knowledge related to IoT and its impact on DT processes at the scale of individuals, organizations and the new way of delivering value to society. This knowledge about researchers, institutions, countries and the derivation is multiple indicators allows improving decision-making at multiple scales on these issues.

The ability of a business to outperform its rivals is known as its competitive edge, and it presents special difficulties in the context of the “digital revolution,” or the fourth industrial revolution. To obtain a competitive edge in the startup operations 4.0 era, this study aims to examine the organizational, technological and competence-related challenges presented by Industry 4.0. It does this by concentrating on the tools, competencies, methods, approaches, tools and strategies that are crucial. Using the Total Interpretive Structural Modeling (TISM) technique, the goal is to find, analyze and classify enablers for startup operations 4.0.

A closed-ended questionnaire and planned interviews were used in the data collection process. In startup operations 4.0, the cross-impact matrix multiplication applied to classification method is used to rank and categorize competitive advantage factors, whereas the TISM technique is used to analyze how components interact.

The study highlights the critical significance of the “Internet of Things (IoT),” “information technologies,” “technological platforms,” “employee empowerment,” “augmented reality (AR)” and “operational technologies” in its identification of 12 enablers for startup operations 4.0.

The main focus of the study is on the variables that affect startup operations 4.0’s competitive advantage.

Academics and important stakeholders can better understand the factors influencing competitive advantage in startup operations 4.0 with the help of this research.

Large businesses have been profoundly impacted by Industry 4.0 principles; however, startup operations 4.0’s competitive advantage has not received as much attention. This paper offers a fresh take on the concept of competitive advantage in startup operations 4.0 research.

One of the most hyped concepts in the manufacturing industry is ‘Industry 4.0’. The ‘Industry 4.0’ concept is grabbing the attention of every manufacturing industry across the globe because of its immense applications. This phenomenon is an advanced version of Industry 3.0, combining manufacturing processes and the latest Internet of Things (IoT) technologies. The main advantage of this paradigm shift is efficiency and efficacy in the manufacturing process with the help of advanced automated technologies. The concept of ‘Industry 4.0’ is contemporary, so it falls under exploratory study. Therefore, the research methodology is thematic narration grounded on secondary data (online) analysis. In this light, this chapter aims to explain ‘Industry 4.0’ in terms of concepts, theories and models based on the Web of Science (WoS) database. The data include research manuscripts, book chapters, blogs, white papers, news items and proceedings. The study details the latest technologies behind the ‘Industry 4.0’ phenomenon, different business intelligence technologies and their practical implications in some manufacturing industries. This chapter mainly elaborates on Industry 4.0 frameworks designed by (1) PwC (2) IBM (3) Frost & Sullivan.