This paper proposes an economical, nonintrusive, and high-precision indoor localization
scheme based on Wi-Fi fingerprinting that requires only a single Wi-Fi access point and a …

With the rapid development of location-based IoT applications in recent years, indoor device-
free passive localization based on Wi-Fi channel state information (CSI) has attracted …

The location-based services for Internet of Things (IoTs) have attracted extensive research
effort during the last decades. Wi-Fi fingerprinting with received signal strength indicator …

Conventional Wi-Fi-based indoor localization methods rely on training a RSS fingerprint
model to predict user locations. Most fingerprinting models only consider the distribution of …

In this paper, we propose a convolutional neural network (CNN) model for device-free
fingerprinting indoor localization based on Wi-Fi channel state information (CSI). Besides …

Wi-Fi Received Signal Strength (RSS) based indoor localization is promising and widely
investigated due to the pervasive deployment of Wi-Fi Access Points (APs). However, one …

Localization is of key importance to a variety of applications. Most previous approaches
require the objects to carry electronic devices, while on many occasions device-free …

Indoor localization is emerging as an important application domain for enhanced navigation
(or tracking) of people and assets in indoor locales such as buildings, malls, and …

Device-free Passive (DfP) indoor localization releases the users from the burden of wearing
sensors or carrying smartphones. Instead of locating devices, DfP technology directly …

Device-free Wi-Fi indoor localization has received significant attention as a key enabling
technology for many Internet of Things (IoT) applications. Machine learning-based location …