Artificial Intelligence and Machine Learning for the Industrial Internet of Things (IIoT)

Abstract

The Internet, presently, is moving toward Internet of Things (IoT) from its dimension of Internet of Computers (IoC). The IoT provides the opportunity for users to retrieve real-time data of every operation carried out physically in a business, intruding almost all the global economic sectors. The sensors, connected via wireless network to gather and share data, which are embedded to the devices in the industries, refer to the term Industrial Internet of Things (IIoT). In simple terms, IIoT is the application of IoT to the industrial sector, but both have dissimilarities between them. IoT devices are mainly focused on making an individual's life easier and fun, whereas IIoT involves in the efficient business process. The whole data from the IIoT sensors could be collected and analyzed for an efficient business process and also can be applied for better decision making. Further, the analysis of real-time data from IIoT assists business organizations to provide an intuition into their supply chain, leading them to achieve the core competencies and competitive advantage. Tactile IoT/IIoT is the next generation of IoT and IIoT. It combines together the technologies of hyperconnectivity, edge computing, artificial intelligence (AI), and machine learning (ML). Industrial 4.0 revolution heavily depends on operational technology in order to make changes in all the industries and their applications. Earlier, fog and edge computing were applied for IIoT, so that connectivity could be provided within Industry 4.0. But now, another interconnected component “analytics” has been added to the IIoT technology, which is achieved by the application of AI and ML algorithms. AI plays a dynamic role in the development and deployment of IIoT applications. With recent advancements in science and technology, especially in ML, business organizations are embracing complex and ample strategies for data analysis. Integration of AI technologies along with IIoT in business organizations paves the way to comprehend the complete potential of enabling IIoT. This will facilitate the smart devices for intelligent behavior simulation and to make better business decisions, with or without the help of a human. AI in IIoT networks is becoming one of the key components for a successful digital ecosystem, which are based on IIoT. Hence, AI and ML are the present driving force for the smart industrial revolution. This study focuses on the application of AI and ML algorithms in the context of IIoT.