Abstract

Industry 4.0 provides emergence to what is called the “Smart Factory.” Industry 4.0 (IR 4.0) is a growing phenomenon for automation and information sharing in industrial technology. Artificial-intelligence-based methods (i.e., deep learning and machine learning) play a crucial role within IR 4.0. The main component of IR 4.0 includes a sensor, robotics, smart cameras, and software integration to manage the central system. These sensors generate huge amounts of data. This chapter examines the effect of numerous machine learning and deep-learning technologies on IR 4.0. The work also proposes a hybrid machine learning and deep learning-based model (HMDL) for IR4.0. The proposed HMDL model utilizes the features of the random forest machine learning method and the multilayer perceptron networks of the deep learning method. The importance of machine and deep learning strategies for Industry 4.0 is addressed further, as well as their application to problems in industrial production. Finally, the recent state-of-the-art object-tracking process is described, including the possible outcomes and future growth prospects.

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