… , which utilizes edge computing to migrate the deep learning … to optimize the deep learning
model so that its requirements for … Internet of Things,” IEEE Internet Things J., vol. 5, no. 4, pp. …

… To maximize the number of successful transmissions in each time slot, we model this problem
as unsupervised learning, where the perfect channel state information (CSI) is assumed to …

… learning in industrial Internet of Things,” IEEE Internet Things … industrial Internet of
Things based on deep learning models,” … Giannetti, “A deep learning model for smart manufacturing …

… This is the motivation of utilizing deep learning models in this study, due to their ability of
the automatic feature extracting with a depth analysis to network data and detecting outlier …

… learning technique to the task of IIoT component recognition. We use the known VGG-16
model and leverage T-Less industrial … learning framework for IoT,” IEEE Internet Things J., vol. 8…

The Industrial Internet of Things (IIoT) is a recent research area that links digital equipment
and services to physical systems. The IIoT has been used to generate large quantities of data …

… , dynamic, and inharmonious data in Industrial Internet of Things (IIoT) platforms. Such vast
… detection models less effective to operate. In this paper, an ensemble deep learning model …

… This data pipeline helps us build machine learning models on batch historic data as well
as streaming live data. While batch data analytics helps us identify problems in manufacturing …

… learning enabled trust-boundary protection for adversarial industrial IoT environment,” IEEE
Internet Things … using deep-learning feature extraction-based semi-supervised model,” IEEE …

… We have used the Keras library [40] to build the ANN, and for the other algorithms, the
scikit-learn library [41] was utilized to develop the learning models for the IDS. The models are …