As an important biomarker for human identification, human gait can be collected at a
distance by passive sensors without subject cooperation, which plays an essential role in …

Abstract Mobile Edge Computing (MEC) is a modern paradigm that involves moving
computing and storage resources closer to the network edge, reducing latency, and …

Deep neural networks have empowered accurate device-free human activity recognition,
which has wide applications. Deep models can extract robust features from various sensors …

WiFi-based smart human sensing technology enabled by Channel State Information (CSI)
has received great attention in recent years. However, CSI-based sensing systems suffer …

Recently, with the advancement of the Internet of Things (IoT), WiFi CSI-based HAR has
gained increasing attention from academic and industry communities. By integrating the …

The past decade has demonstrated the potential of human activity recognition (HAR) with
WiFi signals owing to non-invasiveness and ubiquity. Previous research has largely …

Passive sensing technology enables Wi-Fi-based human activity recognition (HAR), which
has been widely noted in recent years. This letter presents a novel Wi-Fi-based class …

Wireless sensing has emerged as a dynamic field with diverse applications across smart
cities, healthcare, the internet of things (IoT), and virtual reality gaming. This burgeoning …

Federated Learning (FL) enables distributed training of human sensing models in a privacy-
preserving manner. While promising, federated global models suffer from cross-domain …

Accurate indoor pedestrian localization and tracking are crucial in many practical
applications. One efficient yet low-cost sensing scheme is the integration of inertial …