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A Data Set Accuracy Weighted Random Forest Algorithm for IoT Fault Detection Based on Edge Computing and Blockchain
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DOI：10.1109/JIOT.2020.3044934.png)
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Abstract
En 中文
The continuously increasing number of connected smart devices has led to the emergence of a crucial fault detection challenge to the Internet of Things (IoT). In this study, we aim to identify a method for the effective detection of faults in IoT devices. An IoT network model is first established, and a data edge verification mechanism based on blockchain is proposed; the blockchain is used to ensure that the data cannot be tampered with, and their accuracy is verified using the edge. Finally, a data set accuracy weighted random forest based on particle swarm optimization is proposed. The simulation results demonstrate that the proposed detection algorithm is both effective and efficient.
Keywords:
Logic gates
Internet of Things
Blockchain
Fault detection
Cloud computing
Image edge detection
Distributed databases
Blockchain
edge computing
fault detection
Internet of Things (IoT)
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