A Comprehensive Literature Review on Data Analytics in IIoT (Industrial Internet of Things)

Author Name(s): B Ramasubba Reddy*, A V L N Sujith
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IoT (Internet of Things) is the paradigm in which efforts are being made to enable seamless processing of information by integrating physical and digital world devices that can be used ubiquitously. Integration of IoT and cloud computing is the major research area where the data collected from the various high data rate sensors and aggregated with data obtained by cloud-enabled services further which is delivered to the end users in an effective way. Analytical mechanisms like predictive analysis, machine learning algorithms are applied to examine and derive conclusions from the Bigdata gathered from various sources. With the advent of IIoT (Industrial Internet of Things) which is primarily concerned with IoT applications developed for the manufacturing industry, generates a huge amount of data at a greater speed where there is a need for effective data analytics. This paper provides an outline of various architectural components of IIoT and enables with a comprehensive review of various research studies addressing Big data analytics in IIoT. Furthermore, it includes contemporary technological challenges to develop IIoT systems.


Over the past two centuries, the humankind has experienced several waves of innovations of those four major innovations are remarkable for their existence. In the timeline of the eighteenth-century evolution of steam engine in the production and manufacturing enabled a path for Industrial revolution. Further, in the 20th-century advent of the electricity, it has accelerated the process of industrial evolution. Furthermore, in the decade of considered as the appliance of standard concept of Cyber-Physical systems in which data from several industrial viewpoints are closely collected and monitored from the physical space moreover synchronized with the cyberspace. The revelation of the Industrial Internet closely depends on the procedure of adopting advanced information as well as the communication technologies in manufacturing industries. Numerous streams of technologies are enabled in the Industrial Internet, that includes industrial sensing, networking, and control, big data, cloud computing, data analytics, and security, etc. These technologies include diverse features of the industrial manufacturing as well as the production process with sensing, connection storage, analytics,  automation storage, sensing, connection, automation, machine intelligence, and manufacturing. Nowadays the sensor technology is significantly decreased in terms of size as well as the cost making the Internet which is defined as a network of networks that connects several computers. The integration of Industrial and Internet revolution provide the foundation for Industrial Internet revolution.


There is a drastic increase in the data production over the past few decades with the large number of sensor and smart devices acquired from distributed data sources. Industrial Internet of Things endow with a convenient and a viable service to develop applications in the context of building intelligent industry. Massive data acquired from IIoT deployment, results in the wastage of resources during the data transmission process. Data obtained from IIoT deployment will have features like dynamic heterogeneity and polymorphism. This article address the problem of adopting IIoT technology and presents a comprehensive review of various studies that address the stature of IIoT deployment across various application industries. Moreover, this article provides the insights about the potential barriers of implementing IIoT for intelligent industry. There is need for deriving more accurate analytical mechanisms at the edge of the network and it could be a prominent area for further research.


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