Recently, various novel scenarios have been studied for indoor localization. The trilateration
is known as a classic theoretical model of geometric-based indoor localization, with uniform …

The clustering of categorical data is a common and important task in computer science,
offering profound implications across a spectrum of applications. Unlike purely numerical …

Some of the recent developments in data science for worldwide disease control have
involved research of large-scale feasibility and usefulness of digital contact tracing, user …

Indoor positioning with smartphone-compatible technologies has fostered much research
attention in recent years. In this context, Bluetooth Low Energy (BLE) reveals a good …

Abstract Currently, ultra-wideband (UWB)-based localization systems are attracting much
attention due to their high ranging accuracy. It is well known that the relative sensor–source …

This work proposes a new indoor positioning system, named KLIP, that uses the-means
clustering algorithm to split the environment into different sets of log-distance propagation …

Indoor positioning based on IEEE 802.11 wireless LAN (Wi-Fi) fingerprinting needs a
reference data set, also known as a radio map, in order to match the incoming fingerprint in …

For mobile users, the ability to accurately acquire their own location is critical. By locating,
mobile users can get information about their environment and access location-related …

Fingerprint-based indoor localization is one of the most promising solutions for various
Intelligent Internet of Things (IIoT) systems. However, recent studies show that the key …

In modern radio networks with large antenna arrays and precise beamforming techniques,
accurate user positioning plays a key role in enabling seamless mobility management, link …