In the era of the Internet of Things (IoT) and Industry 4.0, the indoor usage of smart devices is
expected to increase, thereby making their location information more important. Based on …

With outstanding features, machine learning (ML) has become the backbone of numerous
applications in wireless networks. However, the conventional ML approaches face many …

Transfer learning (TL) has been successfully applied to many real-world problems that
traditional machine learning (ML) cannot handle, such as image processing, speech …

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 …

Precise occupancy information is extremely valuable for energy savings and optimization in
the built environment. Building management systems (BMSs) can automatically turn off the …

Artificial lighting accounts for a significant proportion (19%) of energy consumption in
building environments. This large contribution calls for the creation of energy-efficient …

Indoor localization has the capability to change the way of providing location-based services
in a closed environment and has more potential than that of GPS if the present shortcomings …

Data-driven paradigms are well-known and salient demands of future wireless
communication. Empowered by big data and machine learning techniques, next-generation …

We propose a gesture recognition system that leverages existing WiFi infrastructures and
learns gestures from channel state information (CSI) measurements. Having developed an …

With the unprecedented advancement of Internet of Things (IoT), automatic occupant activity
recognition is becoming realizable for a myriad of emerging applications in smart buildings …