Indoor localization of mobile nodes is receiving great interest due to the recent advances in
mobile devices and the increasing number of location-based services. Fingerprinting based …

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 …

Learning-based localization plays a significant role in wireless indoor localization problems
over deterministic or probabilistic-based methods. Recent works on machine learning-based …

Wi-Fi Fingerprinting is widely adopted for smartphone-based indoor positioning systems due
to the availability of already deployed infrastructure for communications. The UJIIndoorLoc …

Wi-Fi fingerprint-based indoor localization methods are effective in static environments but
encounter challenges in dynamic, real-world scenarios due to evolving fingerprint patterns …

Indoor location-based services have become very popular, principally, because of its wide
and valuable applications. On that context, Wi-fi fingerprinting based on the received signal …

This research presents an enhanced indoor positioning system using Received Signal
Strength Indicator (RSSI) values and probabilistic matrix factorization within a classroom …

To improve the accuracy of indoor positioning systems it can be useful to combine different
types of sensor data. This paper describes deep learning methods both for estimating …

In recent years, several of the latest communication technologies enable Round Trip Time
(RTT) for positioning in addition to Received Signal Strength (RSS). It is expected to improve …

To perform indoor localization in Internet of Things networks, mobile devices transmit an
extra information. This extra communication increases the energy consumed. In this paper …