Swarm-based and energy-aware unmanned aerial vehicle system for video delivery of mobile objects

I Medeiros, A Boukerche… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Floods are the most common disaster in the world and cause deaths, damages to houses,
buildings, and possessions, as well as disruption to communications. In such dynamic …

Deep Reinforcement Learning Assisted UAV Path Planning Relying on Cumulative Reward mode and Region Segmentation

Z Wang, SX Ng, EIH Mohammed - IEEE Open Journal of …, 2024 - ieeexplore.ieee.org
In recent years, unmanned aerial vehicles (UAVs) have been considered for many
applications, such as disaster prevention and control, logistics and transportation, and …

Synergetic fusion of Reinforcement Learning, Grey Wolf, and Archimedes optimization algorithms for efficient health emergency response via unmanned aerial vehicle

H Gupta, K Sreelakshmy, OP Verma… - Expert …, 2022 - Wiley Online Library
Owing to the recent technological innovations, unmanned aerial vehicles (UAVs) are
progressively employed in various civil and military applications, including healthcare. This …

Trajectory design for effective and secure communication in UAV-WSN systems

F Stoican, D Popescu, L Ichim - … Radio and Antenna Days of the …, 2019 - ieeexplore.ieee.org
Nowadays, unmanned aerial vehicles (UAVs) and wireless sensor networks (WSNs) are
often integrated in collaborative systems for data collection. In this paper, a specific UAV …

Powering UAV with deep Q-network for air quality tracking

AFY Mohammed, SM Sultan, S Cho, JY Pyun - Sensors, 2022 - mdpi.com
Tracking the source of air pollution plumes and monitoring the air quality during emergency
events in real-time is crucial to support decision-makers in making an appropriate …

Research on Multi UAVS Task Allocation Method for Post Disaster Emergency Goods Distribution

L Chen, D Song, S Zhang - Journal of Physics: Conference …, 2023 - iopscience.iop.org
When a natural disaster occurs, ensuring timely and efficient delivery of emergency supplies
to every affected location is crucial in mitigate the losses caused by the disaster. This study …

Reinforcement learning-enabled UAV itinerary planning for remote sensing applications in smart farming

S Pourroostaei Ardakani, A Cheshmehzangi - Telecom, 2021 - mdpi.com
UAV path planning for remote sensing aims to find the best-fitted routes to complete a data
collection mission. UAVs plan the routes and move through them to remotely collect …

Deep Reinforcement Learning-Driven UAV Data Collection Path Planning: A Study on Minimizing AoI

H Huang, Y Li, G Song, W Gai - Electronics, 2024 - mdpi.com
As a highly efficient and flexible data collection device, Unmanned Aerial Vehicles (UAVs)
have gained widespread application because of the continuous proliferation of Internet of …

Deep Reinforcement Learning‐Based UAV Path Planning for Energy‐Efficient Multitier Cooperative Computing in Wireless Sensor Networks

Z Guo, H Chen, S Li - Journal of Sensors, 2023 - Wiley Online Library
Benefiting from the progress of microelectromechanical system (MEMS) technology,
wireless sensor networks (WSNs) can run a large number of complex applications. One of …

Optimizing UAV-UGV coalition operations: A hybrid clustering and multi-agent reinforcement learning approach for path planning in obstructed environment

S Brotee, F Kabir, MA Razzaque, P Roy… - Ad Hoc Networks, 2024 - Elsevier
One of the most critical applications undertaken by Unmanned Aerial Vehicles (UAVs) and
Unmanned Ground Vehicles (UGVs) is reaching predefined targets by following the most …