6 papers
FedADAS: Communication-Efficient Federated Distillation for On-Device Driver Yawn Recognition in Vehicular Networks
Ahmed Mujtaba, Gleb Radchenko, Marc Masana +1
Driver fatigue is a critical safety concern in advanced driver assistance systems. Driver monitoring models trained off-site on static datasets adapt poorly to real-world condition…
YawDD+: Frame-level Annotations for Accurate Yawn Prediction
Ahmed Mujtaba, Gleb Radchenko, Marc Masana +1
Driver fatigue remains a leading cause of road accidents, responsible for 24% of crashes. While yawning serves as an early behavioral indicator of fatigue, existing approaches face…
Federated Distillation on Edge Devices: Efficient Client-Side Filtering for Non-IID Data
Ahmed Mujtaba, Gleb Radchenko, Radu Prodan +1
Federated distillation has emerged as a promising collaborative machine learning approach, offering enhanced privacy protection and reduced communication compared to traditional fe…
SCAREY: Location-Aware Service Lifecycle Management
Kurt Horvath, Dragi Kimovski, Radu Prodan
Scheduling services within the computing continuum is complex due to the dynamic interplay of the Edge, Fog, and Cloud resources, each offering distinct computational and networkin…
Enhancing Traffic Safety with AI and 6G: Latency Requirements and Real-Time Threat Detection
Kurt Horvath, Dragi Kimovski, Stojan Kitanov +1
The rapid digitalization of urban infrastructure opens the path to smart cities, where IoT-enabled infrastructure enhances public safety and efficiency. This paper presents a 6G an…
ADApt: Edge Device Anomaly Detection and Microservice Replica Prediction
Narges Mehran, Nikolay Nikolov, Radu Prodan +4
The increased usage of Internet of Things devices at the network edge and the proliferation of microservice-based applications create new orchestration challenges in Edge computing…