Cloud computing
Researchers at the Chitkara University Institute of Engineering and Technology have published a new report highlighting the impact of artificial intelligence on industrial processes. According to the study, the Industrial Internet of Things is transforming industrial processes by integrating edge, fog, and cloud computing to offer predictive maintenance and reduce
Cloud computing
Investigators at Guru Nanak Dev University have developed a fog-based framework designed to address the rising incidence of heatstroke through efficient, real-time healthcare solutions. The research team leveraged fog computing, cloud computing, and Internet of Things (IoT) sensors to overcome the limitations of traditional cloud computing in handling real-time IoT
Machine learning
Recent research published in IET Circuits, Devices and Systems has shed light on the performance and reliability of various D flip-flop (DFF) architectures, with significant implications for the development of internet of things (IoT) devices and artificial intelligence (AI) systems. The study, conducted by researchers at the School of Engineering,
Machine learning
Researchers at the University of Mosul have found that a machine learning-based approach can effectively identify and mitigate real-time threats in Internet of Things (IoT) systems. The study, published in the Journal of Engineering, suggests that the use of ensemble algorithms, particularly Random Forest, can significantly improve the accuracy and
Machine learning
A new study published in Scientific Reports has explored the potential of soft actor-critic reinforcement learning to optimize power efficiency in Narrowband IoT (NB-IoT) networks. The research, conducted by School of Electronics Engineering, highlights the significance of power efficiency in extending device lifetimes while maintaining performance in the evolving landscape
Data security
Researchers at the Department of Information Technology have published a study on a new hybrid deep learning framework, MCBA-6GNET, designed to secure 6G-enabled IoT ecosystems. The framework combines multi-scale spatial-temporal analysis with self-attention mechanisms to detect anomalies in real-time. Evaluated on two datasets, MCBA-6GNET achieved 99.97% accuracy and 99.
Machine learning
Artificial intelligence and machine learning have taken center stage in combatting the increasing security threats to the Internet of Things (IoT) devices. With the rapid growth of IoT devices, the vulnerability of security has become a pressing concern. Traditional security solutions are no longer sufficient in addressing the heterogeneity, resource
Machine learning
Research from the School of Electrical Engineering has developed a new framework for intelligent warehousing that leverages machine learning and IoT networks to optimize supply chain logistics. The innovation has the potential to reduce mean absolute error in demand forecasting by 32%, mitigate inventory discrepancies by 99.9%, and minimize
Machine learning
Researchers at Xidian University, in collaboration with several institutions, have created a new defense mechanism against Distributed Denial of Service (DDoS) attacks, known as CRH4DDoS. This innovative approach utilizes conflict resolution strategies to integrate heterogeneous data and detect malicious traffic, providing superior performance metrics and minimizing false positive rates. Key
Machine learning
Recent research published in IET Circuits, Devices and Systems has shed light on the performance and reliability of various D flip-flop (DFF) architectures, with significant implications for the development of internet of things (IoT) devices and artificial intelligence (AI) systems. The study, conducted by researchers at the School of Engineering,
Technical institutes
Research conducted at the Technical University of Sofia has unveiled a wireless environmental monitoring system that can collect and analyze environmental parameters in real-time, providing valuable insights for optimizing transportation systems. The system, which utilizes a hybrid, dual-band IoT system based on LoRa and LoRaWAN, is designed to measure air
Technical institutes
Research from Posts and Telecommunications Institute of Technology presents a novel real-time fire detection framework, optimized for resource-constrained edge devices, which achieves high mean average precision for fire and smoke detection. The framework, utilizing the fine-tuned YOLOv10 model and Coral Accelerator, demonstrates exceptional performance and is suitable for low-cost real-time
