Emerging artificial intelligence applications across the domains of computer vision, natural
language processing, graph processing, and sequence prediction increasingly rely on deep …

With the increasing demand for edge device-powered location-based services in indoor
environments, Wi-Fi received signal strength (RSS) fingerprinting has become popular …

The federated distillation (FD) paradigm has been recently proposed as a promising
alternative to federated learning (FL), especially in wireless sensor networks with limited …

The pervasive integration of Indoor Positioning Systems (IPS) arises from the limitations of
Global Navigation Satellite Systems (GNSS) in indoor environments, leading to the …

As a mature indoor positioning solution, fingerprint-based positioning has been widely
applied. However, traditional fingerprint positioning schemes still face the problems of …

Federated learning (FL) has emerged as a crucial technology in today's data-centric
environment, enabling decentralized machine learning while safeguarding user privacy …

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 …

Indoor localization has become increasingly vital for many applications from tracking assets
to delivering personalized services. Yet, achieving pinpoint accuracy remains a challenge …

Indoor navigation is a foundational technology to assist the tracking and localization of
humans, autonomous vehicles, drones, and robots in indoor spaces. Due to the lack of …

Abstract In recent years, Indoor Positioning Systems (IPS) have emerged as a critical
technology to enable a diverse range of Location-based Services (LBS) across different …