A survey of maritime unmanned search system: Theory, applications and future directions

J Li, G Zhang, C Jiang, W Zhang - Ocean Engineering, 2023 - Elsevier
The rising frequency of ocean activities, such as ocean transportation and marine resources
development, inevitably leads to a higher incidence of sudden accidents at sea. Maritime …

Vehicular communication network enabled CAV data offloading: A review

M Ahmed, MA Mirza, S Raza, H Ahmad… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
The connected and autonomous vehicles (CAV) applications and services-based traffic
make an extra burden on the already congested cellular networks. Offloading is envisioned …

Twinport: 5g drone-assisted data collection with digital twin for smart seaports

Y Yigit, LD Nguyen, M Ozdem, OK Kinaci, T Hoang… - Scientific Reports, 2023 - nature.com
Numerous ports worldwide are adopting automation to boost productivity and modernize
their operations. At this point, smart ports become a more important paradigm for handling …

A survey on applications of unmanned aerial vehicles using machine learning

K Teixeira, G Miguel, HS Silva, F Madeiro - IEEE Access, 2023 - ieeexplore.ieee.org
Unmanned Aerial Vehicles (UAVs) play an important role in many applications, including
health, transport, telecommunications and safe and rescue operations. Their adoption can …

A Survey on Air-to-Sea Integrated Maritime Internet of Things: Enabling Technologies, Applications, and Future Challenges

S Liu, L Zhu, F Huang, A Hassan, D Wang… - Journal of Marine Science …, 2023 - mdpi.com
Future generation communication systems are exemplified by 5G and 6G wireless
technologies, and the utilization of integrated air-to-sea (A2S) communication infrastructure …

A review of research on reinforcement learning algorithms for multi-agents

K Hu, M Li, Z Song, K Xu, Q Xia, N Sun, P Zhou, M Xia - Neurocomputing, 2024 - Elsevier
In recent years, multi-agent reinforcement learning techniques have been widely used and
evolved in the field of artificial intelligence. However, traditional reinforcement learning …

Cooperative Data Collection for UAV-Assisted Maritime IoT Based on Deep Reinforcement Learning

X Fu, X Huang, Q Pan, P Pace, G Aloi… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In maritime data collection scenarios, achieving the rapid delivery of data from buoy sensor
nodes to the shipboard station is a challenging issue. Utilizing unmanned aerial vehicles …

DRL-Optimized Optical Communication for a Reliable UAV-Based Maritime Data Transmission

H Luo, S Ma, H Tao, R Ruby, J Zhou… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Maritime data transmission with unmanned aerial vehicles (UAVs) in maritime Internet of
Things (MIoT) systems has received increasing attention due to its flexibility and low cost. To …

Energy-Efficient Flight Scheduling and Trajectory Optimization in UAV-Aided Edge Computing Networks

W Ye, L Zhao, J Zhou, S Xu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Energy saving is a critical issue in UAV-aided edge computing for their limited battery
storage. Most recent studies in UAV-aided edge computing have focused on reducing the …

Collaborative Data Collection in UAV-Enabled Maritime IoT with Constrained Aerial Base Stations

X Fu, M Ren, X Liu - IEEE Sensors Journal, 2024 - ieeexplore.ieee.org
Unmanned aerial vehicle (UAV)-enabled Internet of things (IoT) systems are considered an
effective solution for maritime environmental monitoring. However, in the maritime data …