Magnetic-based indoor localization has attracted considerable attention due to the
pervasiveness of geomagnetic fields and is free of extra infrastructures. However, existing …

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

To increase the sustainability in urban mobility, it is necessary to optimally combine public
and shared vehicles throughout a passenger's trip. In this work, we present a survey on …

Many engineered approaches have been proposed over the years for solving the hard
problem of performing indoor localization using smartphone sensors. However, specialising …

WiFi sensing has been well explored for recognizing human activity types. However,
research is limited in the possibility of its use in identifying affective expressions such as …

Indoor positioning systems have been explored for decades to facilitate universal location-
based services. However, complex environment conditions and sensing imperfections …

Indoor positioning has been widely researched in recent years due to its high demand for
develo** localization services and its complexity in GPS-denied environments. However …

Inertial tracking is vital for robotic IoT and has gained popularity thanks to the ubiquity of low-
cost Inertial Measurement Units (IMUs) and deep learning-powered tracking algorithms …

As the Internet of Things (IoT) industry grows, the risk of network protocol security threats has
also increased. One protocol that has come under scrutiny for its security vulnerabilities is …

In recent years WiFi became the primary source of information to locate a person or device
indoor. Collecting RSSI values as reference measurements with known positions, known as …