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Advanced Predictive Analytics for Control of Industrial Automation Process
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Author(s): Sai Deepthi Bhogaraju (InkforTech, India), Korupalli V Rajesh Kumar (VIT Chennai, India), Anjaiah P. (Institute of Aeronautical Engineering, India), Jaffar Hussain Shaik (KSRM College of Engineering, India)and Reddy Madhavi K. (Sree Vidyanikethan Engineering College, India)
Copyright: 2021
Pages: 17
Source title:
Innovations in the Industrial Internet of Things (IIoT) and Smart Factory
Source Author(s)/Editor(s): Sam Goundar (British University Vietnam, Vietnam), J. Avanija (Sree Vidyanikethan Engineering College, India), Gurram Sunitha (Sree Vidyanikethan Engineering College, India), K. Reddy Madhavi (Sree Vidyanikethan Engineering College, India)and S. Bharath Bhushan (Sree Vidyanikethan Engineering College, Tirupati, India)
DOI: 10.4018/978-1-7998-3375-8.ch003
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Abstract
The recent evolution of the fourth industrial revolution is Industry 4.0, projecting the enhancement of the technology, development, and trends towards the smart processing of the automation in industries. The advancements in communication and connectivity are the major source for the Industrial IoT (IIoT). It collaborates all the industrial functional units to work under a single control channel, digital quantification analytic methods deployment for the prediction of machinery, sensors, monitoring systems, control systems, products, workers, managers, locations, suppliers, and customers. In addition to IIoT, AI methods are also playing a vital role in predictive modeling and analytic methods for the assessment, control, and development of rapid production, from the industries. Other side security issues are challenging the development, concerning all the factors digitalization processes of the industries need to move forward. This chapter focuses on IIoT core concepts, applications, and key challenges to enhance the industrial automation process.
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