Edge Computing (EC) is a new architecture that extends Cloud Computing (CC) services
closer to data sources. EC combined with Deep Learning (DL) is a promising technology …

Systems for monitoring air quality are essential for reducing the negative consequences of
air pollution, but creating real-time systems encounters several challenges. The accuracy …

Abstract Federated Learning (FL), Artificial Intelligence (AI), and Explainable Artificial
Intelligence (XAI) are the most trending and exciting technology in the intelligent healthcare …

The federated learning technique (FL) supports the collaborative training of machine
learning and deep learning models for edge network optimization. Although a complex edge …

Machine learning typically relies on the assumption that training and testing distributions are
identical and that data is centrally stored for training and testing. However, in real-world …

Federated learning (FL) is a hot collaborative training framework via aggregating model
parameters of decentralized local clients. However, most FL methods unreasonably assume …

Abstract Federated Learning (FL, or Collaborative Learning (CL)) has surely gained a
reputation for not only building Machine Learning (ML) models that rely on distributed …

Robotic systems are more connected, networked, and distributed than ever. New
architectures that comply with the de facto robotics middleware standard, ROS 2, have …

Global warming and climate change are responsible for many disasters. Floods pose a
serious risk and require immediate management and strategies for optimal response times …

Federated Learning (FL) is a decentralized learning approach, meaning it learns from data
housed locally on devices such as tablets, cellular phones, and more, and does not collect …