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An Efficient Imbalance-Aware Federated Learning Approach for Wearable Healthcare with Autoregressive Ratio Observation
Widely available healthcare services are now getting popular because of advancements in wearable sensing techniques and mobile edge computing.
UAV Base Station Trajectory Optimization Based on Reinforcement Learning in Post-disaster Search and Rescue Operations
We propose the method to deploy UAVs cooperating with available TBSs as aerial base stations.
Deep Reinforcement Learning Based Multi-Access Edge Computing Schedule for Internet of Vehicle
As intelligent transportation systems been implemented broadly and unmanned arial vehicles (UAVs) can assist terrestrial base stations acting as multi-access edge computing (MEC) to provide a better wireless network communication for Internet of Vehicles (IoVs), we propose a UAVs-assisted approach to help provide a better wireless network service retaining the maximum Quality of Experience(QoE) of the IoVs on the lane.
Clairvoyance: Intelligent Route Planning for Electric Buses Based on Urban Big Data
Nowadays many cities around the world have introduced electric buses to optimize urban traffic and reduce local carbon emissions.
