Analysıs on Industrıal Internet of Thıngs Usıng Cloud and Optımızed Artıfıcal Neural Networks Model Based Engıneerıng
In this paper, an analysis is presented using a machine learning based model-based engineering (ML-MBE) that implements the industrial workflow in cloud-based IIoT. The integrated cloud-based IIoT combines cloud features with open connectivity with IoT. In this research, the validation stages consumes high energy for tracking the reference signal and it requires maximum voltage for the pump. In order to improve the tracking of reference signal with reduced energy and minimum voltage to pump, we use ML algorithm namely Artificial Neural Network (ANN) to optimize the operation in the workflow. The optimized operation in this integrated workflow solves repeatedly the optimization routine to attain the required output.The simulation is conducted to verify the benefits associated with Cloud-IIoT integration with MBE. The proposed method is compared with benchmark method to test the efficacy of the proposed machine learning approach.
Keywords–IIoT, Cloud, ANN, ML-MBE