Internet of Thing
The Internet of Things (IoT) involves connecting billions of devices to collect and analyze data, aiming to improve efficiency and decision-making across various sectors. Current research heavily focuses on enhancing IoT security through machine learning (ML) models like deep neural networks (CNNs, LSTMs, Transformers), federated learning, and the integration of large language models (LLMs) for improved anomaly detection and attack prediction. These advancements are crucial for addressing the growing concerns of data privacy, security vulnerabilities, and resource constraints within increasingly complex IoT networks, impacting fields from smart cities to healthcare.
Papers
Analyzing the Adoption Challenges of the Internet of Things (IoT) and Artificial Intelligence (AI) for Smart Cities in China
Ke Wang, Yafei Zhao, Rajan Kumar Gangadhari, Zhixing Li
Energy-efficient and Privacy-aware Social Distance Monitoring with Low-resolution Infrared Sensors and Adaptive Inference
Chen Xie, Daniele Jahier Pagliari, Andrea Calimera
Optimal service resource management strategy for IoT-based health information system considering value co-creation of users
Ji Fang, Vincent CS Lee, Haiyan Wang
Digital Twin Virtualization with Machine Learning for IoT and Beyond 5G Networks: Research Directions for Security and Optimal Control
Jithin Jagannath, Keyvan Ramezanpour, Anu Jagannath