Learning in the air: Secure federated learning for UAV-assisted crowdsensing
Unmanned aerial vehicles (UAVs) combined with artificial intelligence (AI) have opened a
revolutionized way for mobile crowdsensing (MCS). Conventional AI models, built on …
revolutionized way for mobile crowdsensing (MCS). Conventional AI models, built on …
Drones' edge intelligence over smart environments in B5G: Blockchain and federated learning synergy
Edge Intelligence is an emerging technology which has attracted significant attention. It
applies Artificial Intelligence (AI) closer to the network edge for supporting Beyond fifth …
applies Artificial Intelligence (AI) closer to the network edge for supporting Beyond fifth …
ACP-based modeling of the parallel vehicular crowd sensing system: Framework, components and an application example
As an emerging paradigm for urban sensing, vehicular crowd sensing (VCS) has received
increasing attention in recent years. Unlike traditional sensing paradigms, VCS leverages …
increasing attention in recent years. Unlike traditional sensing paradigms, VCS leverages …
A multi-AGV routing planning method based on deep reinforcement learning and recurrent neural network
Y Lin, G Hue, L Wang, Q Li, J Zhu - IEEE/CAA Journal of …, 2023 - ieeexplore.ieee.org
Dear Editor, This letter presents a multi-automated guided vehicles (AGV) routing planning
method based on deep reinforcement learning (DRL) and recurrent neural network (RNN) …
method based on deep reinforcement learning (DRL) and recurrent neural network (RNN) …
Data-driven stochastic energy management of multi energy system using deep reinforcement learning
Y Zhou, Z Ma, J Zhang, S Zou - Energy, 2022 - Elsevier
The multi energy system (MES) is promising in the process of carbon neutrality, such that
multi energy resources are utilized comprehensively to reduce the operation cost. Another …
multi energy resources are utilized comprehensively to reduce the operation cost. Another …
Cooperative data sensing and computation offloading in UAV-assisted crowdsensing with multi-agent deep reinforcement learning
T Cai, Z Yang, Y Chen, W Chen… - … on Network Science …, 2021 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) can be leveragedin mobile crowdsensing (MCS) to
conduct sensing tasks at remote or rural areas through computation offloading and data …
conduct sensing tasks at remote or rural areas through computation offloading and data …
Energy-efficient UAV crowdsensing with multiple charging stations by deep learning
Different from using human-centric mobile devices like smartphones, unmanned aerial
vehicles (UAVs) can be utilized to form a new UAV crowdsensing paradigm, where UAVs …
vehicles (UAVs) can be utilized to form a new UAV crowdsensing paradigm, where UAVs …
Unmanned era: A service response framework in smart city
The autonomous vehicles (AVs) in smart city, as intelligent mobile robots, are expected to
provide diversified services to facilitate the life of citizens. However, the attributes of the …
provide diversified services to facilitate the life of citizens. However, the attributes of the …
Decentralized task assignment for mobile crowdsensing with multi-agent deep reinforcement learning
C Xu, W Song - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
Task assignment is a fundamental research problem in mobile crowdsensing (MCS) since it
directly determines an MCS system's practicality and economic value. Due to the complex …
directly determines an MCS system's practicality and economic value. Due to the complex …
Intelligent task allocation for mobile crowdsensing with graph attention network and deep reinforcement learning
C Xu, W Song - IEEE Transactions on Network Science and …, 2023 - ieeexplore.ieee.org
Mobile crowdsensing (MCS) leverages crowd intelligence, ie, smart devices and their
owners, to collect data in an intelligent and cost-efficient manner. One of the fundamental …
owners, to collect data in an intelligent and cost-efficient manner. One of the fundamental …