… First, we introduce an FL framework to enable decentralized edge devices to collaboratively
train an anomaly detection model, which can solve the problem of data islands. Second, we …

… data anomaly detection, a novel multi-source multi-dimensional data anomaly detection
scheme based on hierarchical edge … Firstly, a hierarchical edge computing model is proposed to …

… edge IIoT systems to facilitate real-time anomaly detection. Finally, a comprehensive solution
for a trustworthy global AI-enabled IIoT … The performance of real-time anomaly detection is …

… anomaly detection algorithms. To address these issues, we proposed an IIoT-based condition
monitoring system with an edge… as feature vectors on the edge layer to reduce the network …

… on-device collaborative deep anomaly detection model for edge devices in IIoT. … anomaly
detection framework that involves multiple edge devices for collaborative model training in IIoT, …

… on unsupervised anomaly detection for IIoT to enhance … Thus, an anomaly detection model
with the characteristics of … (EATU) anomaly detection framework for IIoT. The framework …

… the high-reliability of edge devices. Hence, fast & accurate anomaly detection (AD) has
become an urgent need via the edge computing of the industrial Internet of Things (IIoT). For this …

… anomalies between the data from multi-source time series. In this paper, we first present an
anomaly detection model in distributed edge … , as to anomaly detection in industrial IoT, there …

… their IIoT-applications in anomaly detection. It is worth mentioning that GNNs can be used
for the three types anomalies, … to local edge computing nodes or IIoT nodes for consequent …

… system, we propose to utilize graph neural networks to fuse the knowledge of topology into
multisource features in non-Euclidean space. The proposed method can be decomposed into …