The demand for a ubiquitous and accurate indoor localization service is continuously
growing. Current solutions for indoor localization usually depend on using the embedded …

In the recent past, we have witnessed the adoption of different machine learning techniques
for indoor positioning applications using WiFi, Bluetooth and other technologies. The …

Indoor localization is one of the key enablers for various application and service areas that
rely on precise locations of people, goods, and assets, ranging from home automation and …

The development of highly accurate deep learning methods for indoor localization is often
hindered by the unavailability of sufficient data measurements in the desired environment to …

Diversity in training data density and environment locality is intrinsic in the real-world
deployment of indoor localization systems and has a major impact on the performance of …

We introduce a novel technique and an associated high resolution dataset that aim to
precisely evaluate wireless signal based indoor positioning algorithms. The technique …

Localization has long been considered as a crucial research problem for pervasive sensing
systems, especially with the arrival of big data era. Various techniques have been proposed …

In this paper, we propose a wireless positioning method based on Deep Learning. To deal
with the variant and unpredictable wireless signals, the positioning is casted in a four-layer …

Location-based services (LBS) have gained increasing importance in our everyday lives
and serve as the foundation for many smartphone applications. Whereas Global Navigation …

Indoor localization has been an important area of research for many years. A more recent
development in this space is towards device-free localization techniques. We present a …