SciRepID

Belum punya Author-ID ?

Judul	Sitasi	Tahun
A Deep Learning Approach to Fault Detection in Industrial IoT Networks (Alfina Herawati, Bagus Setyo) DOI : 10.62951/ijeemcs.v1i2.74 - Volume: 1, Issue: 2, Sitasi : 0 30-Jun-2024 \| Abstrak \| PDF File \| Resource \| Last.06-Aug-2025 Abstrak: Industrial IoT (IIoT) networks, critical for automation and smart manufacturing, are susceptible to faults due to their complexity and the large number of connected devices. This paper introduces a deep learning-based approach for early fault detection in IIoT networks. By leveraging recurrent neural networks (RNNs) and convolutional neural networks (CNNs), the system effectively identifies anomalies in real-time, helping to reduce system downtime and enhance operational efficiency in industrial settings.	0	2024