From sensors to safety: Internet of Emergency Services (IoES) for emergency response and disaster management
The advancement in technology has led to the integration of internet-connected devices and
systems into emergency management and response, known as the Internet of Emergency …
systems into emergency management and response, known as the Internet of Emergency …
Covert communications in air-ground integrated urban sensing networks enhanced by federated learning
Urban sensing is a rapidly growing field that involves gathering real-time data from urban
environments. These smart sensing systems are pivotal in enhancing urban planning …
environments. These smart sensing systems are pivotal in enhancing urban planning …
A NOMA and MRC enabled framework in drone-relayed vehicular networks: Height/trajectory optimization and performance analysis
In this article, we present a drone-relayed vehicular networking architecture, which aims to
improve the achievable data rate of cell-edge vehicles in rural highway scenarios …
improve the achievable data rate of cell-edge vehicles in rural highway scenarios …
A Survey on Air-to-Sea Integrated Maritime Internet of Things: Enabling Technologies, Applications, and Future Challenges
Future generation communication systems are exemplified by 5G and 6G wireless
technologies, and the utilization of integrated air-to-sea (A2S) communication infrastructure …
technologies, and the utilization of integrated air-to-sea (A2S) communication infrastructure …
NOMA-Enhanced Cooperative Relaying Systems in Drone-Enabled IoV: Capacity Analysis and Height Optimization
Using the drone as a cooperative relay (CR) can improve the connectivity of Internet of
Vehicles (IoV) on highways in remote areas. Meanwhile, considering limited spectrum …
Vehicles (IoV) on highways in remote areas. Meanwhile, considering limited spectrum …
A novel policy based on action confidence limit to improve exploration efficiency in reinforcement learning
F Huang, X Deng, Y He, W Jiang - Information Sciences, 2023 - Elsevier
Reinforcement learning has been used to solve many intelligent decision-making problems.
However, reinforcement learning still faces a challenge of the low exploration efficiency …
However, reinforcement learning still faces a challenge of the low exploration efficiency …
Blockchain-Based Secure Storage and Access Control Scheme for Supply Chain Ecological Business Data: A Case Study of the Automotive Industry
S Li, T Zhou, H Yang, P Wang - Sensors, 2023 - mdpi.com
The reliable circulation of automotive supply chain data is crucial for automotive
manufacturers and related enterprises as it promotes efficient supply chain operations and …
manufacturers and related enterprises as it promotes efficient supply chain operations and …
Aerial-Ground Integrated Vehicular Networks: A UAV-Vehicle Collaboration Perspective
Unmanned aerial vehicle mounted base stations (UAV-BSs) are expected to become an
integral component of future intelligent transportation systems, which can provide seamless …
integral component of future intelligent transportation systems, which can provide seamless …
DRL-based federated learning for efficient vehicular caching management
In this study, we present a hybrid deep reinforcement learning (DRL) algorithm, trained
using vehicular federated learning (VFL), specifically tailored for dynamic vehicular networks …
using vehicular federated learning (VFL), specifically tailored for dynamic vehicular networks …
Hybrid machine learning approach for resource allocation of digital twin in UAV-aided internet-of-vehicles networks
In this study, we present a novel approach for efficient resource allocation in a digital twin
(DT) framework for task offloading in a UAV-aided Internet-of-Vehicles (IoV) network. Our …
(DT) framework for task offloading in a UAV-aided Internet-of-Vehicles (IoV) network. Our …