7 papers
FRSICL: LLM-Enabled In-Context Learning Flight Resource Allocation for Fresh Data Collection in UAV-Assisted Wildfire Monitoring
Yousef Emami, Hao Zhou, Miguel Gutierrez Gaitan +2
Uncrewed Aerial Vehicles (UAVs) play a vital role in public safety, especially in monitoring wildfires, where early detection reduces environmental impact. In UAV-Assisted Wildfire…
From Prompts to Protection: Large Language Model-Enabled In-Context Learning for Smart Public Safety UAV
Yousef Emami, Hao Zhou, Miguel Gutierrez Gaitan +3
A public safety Uncrewed Aerial Vehicle (UAV) enhances situational awareness during emergency response. Its agility, mobility optimization, and ability to establish Line-of-Sight (…
ML-ECS: A Collaborative Multimodal Learning Framework for Edge-Cloud Synergies
Yuze Liu, Shibo Chu, Tiehua Zhang +5
Edge-cloud synergies provide a promising paradigm for privacy-preserving deployment of foundation models, where lightweight on-device models adapt to domain-specific data and cloud…
LLM-Enabled In-Context Learning for Data Collection Scheduling in UAV-assisted Sensor Networks
Yousef Emami, Hao Zhou, SeyedSina Nabavirazani +1
Unmanned Aerial Vehicles (UAVs) are increasingly being utilized in various private and commercial applications, e.g., traffic control, parcel delivery, and Search and Rescue (SAR)…
AIC-VDS: Attention-Based In-Context Learning for Joint Velocity Control and Data Collection Scheduling in Multi-UAV-Assisted Pipeline Monitoring
Yousef Emami, Seyedsina Nabavirazavi, Atefeh Hajijamali Arani +5
Uncrewed aerial vehicles (UAVs) are increasingly deployed for autonomous inspection and sensor data collection in large-scale infrastructure monitoring applications, such as pipeli…
FitLight: Federated Imitation Learning for Plug-and-Play Autonomous Traffic Signal Control
Yutong Ye, Yingbo Zhou, Zhusen Liu +4
Although Reinforcement Learning (RL)-based Traffic Signal Control (TSC) methods have been extensively studied, their practical applications still raise some serious issues such as…