A CNN-LSTM model trained on simulated thermal and power data reaches 94% accuracy on a private synthetic dataset, but the practical claim is not supported by real-world validation or a rule-based baseline.
A cyber-physical systems architec- ture for industry 4.0-based manufacturing systems,
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Predictive Failure Detection in Network Hardware Using Thermal Imaging and Deep Learning with Sensor Fusion
A CNN-LSTM model trained on simulated thermal and power data reaches 94% accuracy on a private synthetic dataset, but the practical claim is not supported by real-world validation or a rule-based baseline.