Federated learning (FL) brings collaborative intelligence into industries without centralized
training data to accelerate the process of Industry 4.0 on the edge computing level. FL …

Indoor location-based service is a hot research topic whose application market size is
expected to grow from 41 billion by 2022 and 58 billion by 2023. As a portable …

This article proposes FedPos, a federated transfer learning framework together with a novel
position estimation method for Wi-Fi indoor positioning. Compared with traditional machine …

When fully implemented, sixth generation (6G) wireless systems will constitute intelligent
wireless networks that enable not only ubiquitous communication but also high-accuracy …

Crowdsourced localization plays a significant role for the applications in Internet of Things.
Even though existing studies have proposed privacy-preserving localization algorithms to …

The widespread deployment of machine learning techniques in ubiquitous computing
environments has sparked interests in exploiting the vast amount of data stored on mobile …

Pedestrian navigation activity recognition (PNAR) has a significant impact on positioning
and tracking performance. Smartphone-based PNAR utilizes measurements from sensors …

Privacy-preserving transportation mode identification (TMI) is among the key challenges
toward future intelligent transportation systems. With recent developments in federated …

Fingerprint-based localization plays an important role in indoor location-based services,
where the position information is usually collected in distributed clients and gathered in a …

Localization and tracking of objects using data-driven methods is a popular topic due to the
complexity in characterizing the physics of wireless channel propagation models. In these …