Internet of Things

Purpose: Futurology plays a significant role in advancing organizational goals and mitigating organizational problems and challenges. Therefore, the aim of this study was to identify the dimensions and components of Internet of Things development in schools based on future studies. Methodology: In a descriptive qualitative study, 19 academic and organizational experts from the educational sector of Tehran were interviewed in the academic year 2020-2021 using a semi-structured method. In this study, the sample size was determined according to the principle of theoretical saturation and was selected through purposive sampling. The research tool was a semi-structured interview, whose validity was confirmed through triangulation and whose reliability was calculated at 0.88 using the agreement coefficient between two coders. The data of this study were analyzed using thematic analysis in MAXQDA software, version 2020. Findings: The analysis indicated that the development of the Internet of Things in schools based on future studies encompasses 26 components across 7 dimensions. These dimensions include the elimination of time constraints (with 3 components), elimination of spatial constraints (with 4 components), reduction of infrastructure costs (with 4 components), knowledge management (with 3 components), professional competence (with 3 components), information technology (with 3 components), and effectiveness of the educational system (with 6 components). Ultimately, a thematic network for the development of the Internet of Things in schools based on future studies was established. Conclusion: The model of dimensions and components designed in this study can assist specialists and educational system officials in improving the development of the Internet of Things in schools.

Today, the Internet of Things is a widely recognized phenomenon that generates a significant amount of data and connects many devices. Many products are incorporating electronic components to facilitate their integration and interaction with the Internet. Scalable and efficient trust management systems are required to maintain network reliability, considering the increasing number of IoT devices and generated data. In order to enable scalable trust management in social IoT, this paper presents a sharding-based scalable trust management approach that combines social interactions with smart contract functionality. Through the division of transaction state into smaller segments and the enhancement of trust value propagation among connected devices, sharding techniques in blockchain can offer scalable trust management protocols. When implementing the model on the Hyperledger Fabric platform, we carried out a thorough evaluation. The model calculates trust in terms of trust convergence and success rate efficiently. We have conducted several tests to evaluate the scalability of the model. To boost it, we have also implemented the state sharding. We also conducted a study to highlight the advantages of the sharding strategy on the scalability of the model. The results demonstrate that using shards significantly improves trust management capacity on the blockchain. The proposed method demonstrates the potential application of sharding in blockchain-based Trust Management (TM) for scalable trust management in SIoT.

The Internet of Things (IoT) is a transformative technology that enhances various aspects of human life, significantly impacting fields such as healthcare, industry, transportation, agriculture, education, and commercial applications. In particular, IoT's role in smart healthcare systems has attracted considerable research attention due to its potential to improve patient monitoring, optimize treatments, and reduce costs. Therefore, a systematic assessment of the scientific output in this domain is essential for understanding current trends and future directions. Bibliometric approaches can describe, explain, and predict the scientific contributions of researchers, institutions, journals, and countries on an international scale while identifying emerging research areas. This analysis quantifies scientific output and evaluates its impact through concepts such as co-occurrence networks, collaboration networks, and co-citation networks, revealing trends within specific fields. Given the increasing significance of IoT in healthcare, this study examines trends in IoT applications in medicine using a bibliometric approach. The research analyzes 7,205 articles indexed in the Web of Science (WoS) database, covering the period from 2013 to August 2024. Data visualization was conducted using VOSviewer software. The findings indicate a likely future focus on integrating automated disease detection methods with IoT technologies. China, India, and the United States lead in scientific output, with Asian countries demonstrating a strong interest in healthcare applications. Additionally, security and privacy concerns remain significant challenges in the field.