Purpose: Determining the use of Internet of Things ((IoT)) in selected librariesMethod: This survey used a researcher-made checklist. ؟ ؟experts confirmed the validity of the tool. Websites of twenty libraries as well as the literature about the use of the (IoT) by them were examined. Also we contacted with relevant people in the target libraries to receive additional data. Types of libraries, services provided by (IoT) technologies and tools were investigated.Findings: The libraries benefited from 1) Radio wave identification technology (RFID); 2) Bluebeam technology; 3) Smart camera 4) Smart public areas project; 5) Hui Wen library information service system; 6) Montreal; 7) Book robot; 8) Smart robot; 9) Car to Car communication; 10) Capira mobile application is used to provide services. Bluebeam technology provided users with widest range of all the 10 services. Hui Wen's library information service system by benfiting from eight applications came top in using (IoT).Conclusion: The very fact that libraries studied continue to use (IoT), may suggest that Iranian libraries should consider employing this emerging technology

Context: The Internet of Things ((IoT)) is a system of wireless, interconnected and digital devices that can collect and store data in a network without needing to establish human-to-human or human-to-computer interactions. Objectives: Due to the importance of adopting up-to-date technologies in hospitals and health centers, this systematic review aimed to explore all aspects of the (IoT) applicable in hospitals. Methods: The present study was a systematic review conducted in 4 August 2021 according to PRISMA guidelines. The Internet searches were performed to access three scientific databases of PubMed, Scopus, and ISI Web of Science using a combination of keywords, such as the (IoT) and hospital. Finally, the required data were extracted from original research articles investigating the (IoT) application in hospitals and were entered into EndNote X8 software. Quality assessment of the studies was carried out by two researchers independently. Results: A total of 18 articles were included in the study. The application of (IoT) had been introduced by 13 articles as an effective method in reducing and controlling dust levels as well as improving the quality of health in wards. Moreover, the possibility of using and installing (IoT) systems on mobile phones as well as their application for monitoring health improvement had been investigated by two articles. The advantages of using the (IoT) to save time and keep users’ information confidential had also been discussed by some other reviewed articles. Conclusions: It was concluded that the application of (IoT) system in hospitals increased the quality of healthcare and improved the patient satisfaction. It was also found that adopting (IoT) technology may have been extremely effective in controlling various hospital infections. Moreover, this technology was detected to have the true potential for improving the security of devices and databases in the hospital. Overall, the application of (IoT) was confirmed to increase the efficiency of hospitals and health centers.

(IoT) is a dynamic network of interconnected Things that communicate and exchange data, where security is a significant issue. Previous studies have mainly focused on attack classifications and open issues rather than presenting a comprehensive overview on the existing threats and vulnerabilities. This knowledge helps analyzing the network in the early stages even before any attack takes place. In this paper, the researchers have proposed different security aspects and a novel Bayesian Security Aspects Dependency Graph for (IoT) (BSAG(IoT)) to illustrate their relations. The proposed BSAG(IoT) is a generic model applicable to any (IoT) network and contains aspects from five categories named data, access control, standard, network, and loss. This proposed Bayesian Security Aspect Graph (BSAG) presents an overview of the security aspects in any given (IoT) network. The purpose of BSAG(IoT) is to assist security experts in analyzing how a successful compromise and/or a failed breach could impact the overall security and privacy of the respective (IoT) network. In addition, root cause identification of security challenges, how they affect one another, their impact on (IoT) networks via topological sorting, and risk assessment could be achieved. Hence, to demonstrate the feasibility of the proposed method, experimental results with various scenarios has been presented, in which the security aspects have been quantified based on the network configurations. The results indicate the impact of the aspects on each other and how they could be utilized to mitigate and/or eliminate the security and privacy deficiencies in (IoT) networks.