Robust fault recognition and correction scheme for induction motors using an effective IoT with deep learning approach

•The uncertainties due to the cyberattacks are tackled with a low computation burden deep learning algorithm.•A new IoT structure for monitoring the induction motor is developed.•A graphical visualization is performed to identify the faults of the induction motors.•Parameterizing the DNN of the fault recognition model is investigated.•The results confirm the robustness and resiliency of the designed model.