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.

中文翻译：

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基于边缘计算和区块链的数据集精度加权随机森林算法在物联网故障检测中的应用

不断增长的连接智能设备数量导致对物联网（IoT）的关键故障检测挑战的出现。在这项研究中，我们旨在确定一种有效检测IoT设备故障的方法。首先建立了物联网网络模型，提出了基于区块链的数据边缘验证机制。区块链用于确保数据不会被篡改，并使用边缘验证其准确性。最后，提出了一种基于粒子群算法的数据集精度加权随机森林。仿真结果表明，该算法是有效的。