Artificial intelligence in the IoT era: A review of edge AI hardware and software
T Sipola, J Alatalo, T Kokkonen… - 2022 31st Conference …, 2022 - ieeexplore.ieee.org
The modern trend of moving artificial intelligence computation near to the origin of data
sources has increased the demand for new hardware and software suitable for such …
sources has increased the demand for new hardware and software suitable for such …
Communication-efficient federated learning for digital twin edge networks in industrial IoT
Y Lu, X Huang, K Zhang, S Maharjan… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The rapid development of artificial intelligence and 5G paradigm, opens up new possibilities
for emerging applications in industrial Internet of Things (IIoT). However, the large amount of …
for emerging applications in industrial Internet of Things (IIoT). However, the large amount of …
Secure and scalable blockchain-based federated learning for cryptocurrency fraud detection: A systematic review
With the wide adoption of cryptocurrency, blockchain technologies have become the
foundation of such digital currencies. However, this adoption has been accompanied by a …
foundation of such digital currencies. However, this adoption has been accompanied by a …
A survey on the optimization of neural network accelerators for micro-ai on-device inference
Deep neural networks (DNNs) are being prototyped for a variety of artificial intelligence (AI)
tasks including computer vision, data analytics, robotics, etc. The efficacy of DNNs coincides …
tasks including computer vision, data analytics, robotics, etc. The efficacy of DNNs coincides …
Efficient federated learning for cloud-based AIoT applications
As a promising method for central model training on decentralized device data without
compromising user privacy, federated learning (FL) is becoming more and more popular in …
compromising user privacy, federated learning (FL) is becoming more and more popular in …
Optimizing deep neural networks on intelligent edge accelerators via flexible-rate filter pruning
While deep learning has shown superior performance in various intelligent tasks, it is still a
challenging problem to deploy sophisticated models on resource-limited edge devices. Filter …
challenging problem to deploy sophisticated models on resource-limited edge devices. Filter …
A survey of state-of-the-art on edge computing: Theoretical models, technologies, directions, and development paths
B Liu, Z Luo, H Chen, C Li - IEEE Access, 2022 - ieeexplore.ieee.org
In order to describe the roadmap of current edge computing research activities, we first
address a brief overview of the most advanced edge computing surveys published in the last …
address a brief overview of the most advanced edge computing surveys published in the last …
Comparative analysis of edge computing and edge devices: key technology in IoT and computer vision applications
M Rohith, A Sunil - 2021 International Conference on Recent …, 2021 - ieeexplore.ieee.org
Edge computing is a new emerging technology which focuses on finding computation power
near Internet of Things (IoT) devices such as sensors, smart phones, and many more …
near Internet of Things (IoT) devices such as sensors, smart phones, and many more …
Embedded streaming principal components analysis for network load reduction in structural health monitoring
Principal component analysis (PCA) is a well-established approach commonly used for
dimensionality reduction. However, its computational cost and memory requirements …
dimensionality reduction. However, its computational cost and memory requirements …
A review of AI edge devices and lightweight CNN deployment
Abstract Artificial Intelligence of Things (AIoT) which integrates artificial intelligence (AI) and
the Internet of Things (IoT), has attracted increasing attention recently. With the remarkable …
the Internet of Things (IoT), has attracted increasing attention recently. With the remarkable …