This systematic literature review employs the Preferred Reporting Items for Systematic
Reviews and Meta-Analyses (PRISMA) methodology to investigate recent applications of …

The integration of wireless antenna sensors for cyber-physical systems has become
increasingly prevalent in various biosimilar applications due to the escalating need for …

In recent years, indoor positioning systems (IPSs) have received attention from many
research fields, such as robotics, navigation, human–computer interaction, etc. However …

Multimodal federated learning (FL) aims to enrich model training in FL settings where
devices are collecting measurements across multiple modalities (eg, sensors measuring …

Detecting human activity through cameras and machine learning methods raises significant
privacy concerns, while alternatives like thermal cameras can be expensive. Passive …

Recognition of human locomotor activities is crucial for monitoring the motion patterns.
Current studies for human locomotor activities recognition focused on detecting basic motion …

Multimodal federated learning (FL) aims to enrich model training in FL settings where clients
are collecting measurements across multiple modalities. However, key challenges to …

Combining skeleton and RGB modalities in human action recognition (HAR) has garnered
attention due to their ability to complement each other. However, previous studies did not …

Machine learning (ML) algorithms are now part of everyday life, as many technological
devices use these algorithms. The spectrum of uses is wide, but it is evident that ML …

Abstract Machine learning (ML) systems that utilize sensor inputs have become integral in
various applications; however, they remain vulnerable to sensor-based adversarial example …