9 citations · 13 across the 5 of their papers we have counts for
5 papers
A Privacy-Preserving Indoor Localization System based on Hierarchical Federated Learning
Masood Jan, Wafa Njima, Xun Zhang
Location information serves as the fundamental element for numerous Internet of Things (IoT) applications. Traditional indoor localization techniques often produce significant erro…
Transfer Learning for VLC-based indoor Localization: Addressing Environmental Variability
Masood Jan, Wafa Njima, Xun Zhang +1
Accurate indoor localization is crucial in industrial environments. Visible Light Communication (VLC) has emerged as a promising solution, offering high accuracy, energy efficiency…
MetaGraphLoc: A Graph-based Meta-learning Scheme for Indoor Localization via Sensor Fusion
Yaya Etiabi, Eslam Eldeeb, Mohammad Shehab +4
Accurate indoor localization remains challenging due to variations in wireless signal environments and limited data availability. This paper introduces MetaGraphLoc, a novel system…
FeMLoc: Federated Meta-learning for Adaptive Wireless Indoor Localization Tasks in IoT Networks
Yaya Etiabi, Wafa Njima, El Mehdi Amhoud
The rapid growth of the Internet of Things fosters collaboration among connected devices for tasks like indoor localization. However, existing indoor localization solutions struggl…
Federated Learning based Hierarchical 3D Indoor Localization
Yaya Etiabi, Wafa Njima, El Mehdi Amhoud
The proliferation of connected devices in indoor environments opens the floor to a myriad of indoor applications with positioning services as key enablers. However, as privacy issu…