This letter develops a federated learning (FL) framework for indoor localization using
channel state information (CSI) fingerprint, aiming to (a) design a FL framework for multiple …

Existing traffic flow prediction frameworks have already achieved enormous success due to
large traffic datasets and capability of deep learning models. However, data privacy and …

Abstract Cyber-Physical Systems (CPSs) are systems formed of integrating computation
technologies with traditional embedded physical systems. CPS increases the efficiency of …

Federated Learning (FL) is a distributed Machine Learning (ML) framework, which has been
considered as a reliable approach to preserve privacy for the widely used Internet of Things …

Bayesian data fusion for distributed learning by Peng Wu Doctor of Philosophy in Electrical
and Computer Engineering Northeastern University, April 2024 Prof. Pau Closas, Advisor …

The Internet of Things (IoT) is one of the most in-demand technologies due to its ability to
simplify complex tasks through low-cost devices connected to the internet. Indoor positioning …

Wireless sensor networks (WSNs) require precise node location in order to function
properly, and they are essential in many different applications. In this research, we propose …

O número de dispositivos da (Internet of Things-IoT) cresceu exponencialmente nos últimos
anos, resultando em uma grande massa de dados útil para aplicações de aprendizado de …

Nowadays, indoor positioning is an attractive topic because it allows putting in the
customer's position several services that facilitate indoor life. Otherwise, the indoor …

The prediction of traffic behavior by using indicators such as speed, flow, and density is the
primary research field for intelligent transportation systems. However, the growing …