Channel state information (CSI)-based fingerprinting via neural networks (NNs) is a
promising approach to enable accurate indoor and outdoor positioning of user equipment …

This paper studies a WiFi indoor localisation technique based on using a deep learning
model and its transfer strategies. We take CSI packets collected via the WiFi standard …

With the popularization of machine learning (ML) techniques and the increased chipset's
performance, the application of ML to pedestrian localization systems has received …

Improving sustainability, enhancing spectral and energy efficiency, and bringing in-network
intelligence and reasoning are the driving forces for 6G. In this context, semantic …

Wireless sensing technology allows for non-intrusive sensing without the need for physical
sensors worn by the target, enabling a wide range of applications, such as indoor tracking …

Abstract Bluetooth Low Energy (BLE) has emerged as one of the reference technologies for
the development of indoor localization systems, due to its increasing ubiquity, low-cost …

Bluetooth Low Energy (BLE) has emerged as one of the reference technologies for the
development of indoor localization systems, due to its increasing ubiquity, low-cost …

Traditional approaches to activity recognition involve the use of wearable sensors or
cameras in order to recognise human activities. In this work, we extract fine-grained physical …

Radio signal-based (indoor) localisation technique is important for IoT applications such as
smart factory and warehouse. Through machine learning, especially neural networks …

Traditional approaches to activity recognition involve the use of wearable sensors or
cameras in order to recognise human activities. In this work, we extract fine-grained physical …