In this work, we present a Distributed Bayesian Inference Classifier for Large-Scale Systems,
where we assess its performance and scalability on distributed environments such as …

In this paper, we propose an architecture, design and build a prototype of a novel IoT system
with intelligence, distributed at multiple tiers including the network edge. Our proposed …

As the number of interconnected devices increases and more artificial intelligence (AI)
applications upon the Internet of Things (IoT) start to flourish, so does the environmental cost …

As Artificial Intelligence of Things (AIoT) has become increasingly important for modern AI
applications, federated learning (FL) is envisioned to be the enabling technology for AIoT …

New applications such as smart homes, autonomous vehicles are leading an increasing
research topic of convolutional neural network (CNN) based inference on IoT edge devices …

While existing strategies to execute deep learning-based classification on low-power
platforms assume the models are trained on all classes of interest, this paper posits that …

Modern Internet of Things (IoT) systems are highly complex due to its mobile, ad-hoc and
geographically distributed nature. Very often, an edge-cloud infrastructure is established to …

Recent years have seen an exploration of data volumes from a myriad of IoT devices, such
as various sensors and ubiquitous cameras. The deluge of IoT data creates enormous …

Exploiting big data knowledge on small devices will pave the way for building truly cognitive
Internet of Things (IoT) systems. Although machine learning has led to great advancements …

Artificial intelligence (AI) has witnessed a substantial breakthrough in a variety of Internet of
Things (IoT) applications and services, spanning from recommendation systems and speech …