The increasing demand for energy-efficient and interconnected smart buildings, particularly in the tourism sector, has driven the adoption of advanced wireless technologies. IoT technologies are crucial in this evolution, improving modern buildings’ functionality and operational efficiency. This study investigates the utilization of various wireless technologies within Wireless Personal Area Networks (WPANs), including Bluetooth BLE 4.2, Bluetooth BLE 5.0, ZigBee, and Z-Wave, in smart buildings. A multiple-criteria decision-making (MCDM) approach, specifically the PIPRECIA-S model, was applied to evaluate these technologies based on criteria such as device connectivity, mobility, low energy consumption, scalability, flexibility, and interoperability. Simulations using the PIPRECIA-S model were conducted to assess technology performance across various real-world scenarios. The results indicate that ZigBee (0.2942) and Bluetooth BLE 5.0 (0.2602) provide superior performance in terms of energy efficiency and scalability, followed by Z-Wave (0.2550) and Bluetooth BLE 4.2 (0.1906). These findings provide decision-makers with data-driven recommendations for selecting the most suitable wireless technologies for smart buildings.

Computer Vision Syndrome (CVS) is a highly prevalent syndrome today, yet it remains relatively understudied, leading to limited awareness among users about this syndrome and its preventive measures. This study aims to draw attention to this syndrome among authors and researchers and encourage further research in this area. Data were retrieved from the databases PubMed, Lens, Scopus, and Google Scholar, compiling existing articles and publications from the CVS domain. Analyses cover the period from 1 January to 31 December 2023. Zotero 6.0.27, VOSviewer 1.6.20, and Microsoft Excel software were used for data analysis. A total of 893 papers were reviewed, with 578 papers included in our analysis. The study presents five different analyses showing top authors and publishers, publication trends over the years, as well as papers by source, and, finally, the most frequently used keywords. The results highlight trends in various aspects related to this issue, through the analysis of published articles over the years, along with prominent authors and their respective countries. The focus of this research is on computer vision syndrome and its representation in scientific databases. What is clearly evident from this study is the increasing trend in research over the years, as well as the leading countries in these studies. However, it is also apparent that further research in this area is needed to bring new insights to researchers and raise awareness among users who encounter computers in their daily work.