The advances and convergence in sensor, information processing, and communication
technologies have shaped the Internet of Things of today. The rapid increase of data and …

Progress is being made to deploy convolutional neural networks (CNNs) into the Internet of
Things (IoT) edge devices for handling image analysis tasks locally. These tasks require low …

In deep convolutional neural networks (DCNNs), model size and computation complexity
are two important factors governing throughput and energy efficiency when deployed to …

Convolutional neural network (CNN) is widely deployed on edge devices, performing tasks
such as objective detection, image recognition and acoustic recognition. However, the …

The Internet of Things, privacy, and technical constraints increase the demand for edge-
based data-driven services, which is one of the major goals of Industry 4.0 and Society 5.0 …

This paper presents a survey of functional programming languages in System-on-a-Chip
(SoC) design. The motivation is improving the design productivity by better source code …

Edge–cloud collaboration integrated with network virtualization is indispensable for
diversified edge services. Meanwhile, the multilayer elastic optical network (ML-EON) is a …

The Internet of Things (IoT)-enabled applications use sensors and actuators to collect big
data, which are processed by big data models, eg, Spark. Generally, data processing tasks …

Domain specific hardware architectures and hardware accelerators have been a vital part of
modern system design. Especially for math intensive applications involving tasks related to …

Artificial Internet of Things (AIoT) is a new integrated area of research developed with a
combination of Artificial Intelligence (AI) and Internet of Things (IoT) networks for sensing …