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Advances in 5G and the Internet of Things (IoT) have to cater to the diverse and varying needs of different stakeholders, devices, sensors, applications, networks, and access technologies that come together for a dedicated IoT network for a synergistic purpose. Therefore, there is a need for a solution that can assimilate the various requirements and policies to dynamically and intelligently orchestrate them in the dedicated IoT network. Thus we identify and describe a representative industry-relevant use case for such a smart and adaptive environment through interviews with experts from a leading telecommunication vendor. We further propose and evaluate candidate architectures to achieve dynamic and intelligent orchestration in such a smart environment using a systematic approach for architecture design and by engaging six senior domain and IoT experts. The candidate architecture with an adaptive and intelligent element ("Smart AAA agent") was found superior for modifiability, scalability, and performance in the assessments. This architecture also explores the enhanced role of authentication, authorization, and accounting (AAA) and makes the base for complete orchestration. The results indicate that the proposed architecture can meet the requirements for a dedicated IoT network, which may be used in further research or as a reference for industry solutions.
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http://dx.doi.org/10.3390/s22083017 | DOI Listing |
Sensors (Basel)
July 2025
School of Ocean Informattion Engineering, Jimei University, Xiamen 361000, China.
Resource-constrained Internet of Things (IoT) devices demand efficient and robust intrusion detection systems (IDSs) to counter evolving cyber threats. The traditional IDS models, however, struggle with high computational complexity and inadequate feature extraction, limiting their accuracy and generalizability in IoT environments. To address this, we propose FFT-RDNet, a lightweight IDS framework leveraging depthwise separable convolution and frequency-domain feature fusion.
View Article and Find Full Text PDFSingle-pixel imaging, as a novel computational imaging method, boasts high sensitivity and interference resistance, offering significant application potential. This paper addresses the noise robustness requirements for real-time imaging environments in current single-pixel imaging systems. A hardware-amenable PnP-ADMM algorithm and its corresponding IP core were developed for implementation in an SPI hardware system.
View Article and Find Full Text PDFJ Vis Exp
June 2025
Department of Management, College of Business Administration, Princess Nourah Bint Abdulrahman University.
Cyber-Physical System (CPS) blends computational intelligence with physical processes, which enables instant monitoring, decision-making capability, and automation services throughout various vital domains. Moreover, Generative Artificial Intelligence (AI) faces considerable barriers to deployment within CPS because distributed environments with sensitive data present serious privacy and security maintenance challenges. Current techniques, such as Federated Learning (FL), encounter difficulties both in their model diversity and the risk that privacy may be compromised.
View Article and Find Full Text PDFMethodsX
December 2025
CSE, NIT Goa, Cuncolim, Goa, India.
The method proposed explores the integration of Internet of Things (IoT) technologies and sensor fusion techniques into modern transportation systems to enhance efficiency, safety, and road quality assessment. The study not only emphasizes the importance of V2V communication using DSRC Dedicated Short Range Communication, Threshold Based Algorithms (TBA) and Dynamic Time Warping (DTW) but also proposes a novel approach of IoT multi-sensor fusion hardware model that is designed to identify clean and rough surface road conditions. By deploying multi sensor module into proposed model, real-time road surface data is collected and processed to classify them into flat clean or bumpy rough categories based on their smoothness index.
View Article and Find Full Text PDFSci Rep
July 2025
Information Technology Department, Faculty of Computers and Information Technology, University of Tabuk, KSA,, Tabuk, Saudi Arabia.
Wireless Body Area Networks (WBANs) play a critical role in real-time healthcare monitoring by enabling continuous data collection from body-worn sensors. However, energy inefficiency and data security vulnerabilities limit their large-scale deployment and long-term reliability. The primary aim of this research is to optimize both energy consumption and data integrity within WBAN-based health monitoring systems.
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