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.
TopIntroduction
Internet of Things is a network that connects mechanical, digital, and computing machines with the least human-computer interaction. In 1982, a Coca Cola vending machine at Carnegie Mellon University was the first machine connected via the internet and it was designed to know if the cool drinks in the vending machine are cool without the need for a physical check. Later in 1990, an Internet controlled toaster was built by John Romkey which switches on and off the toaster automatically without human interaction. Father of IoT Kevin Ashton, the Executive Director of Auto-ID Labs at MIT first introduced the term IoT in the presentation designed for Procter & Gamble in the year 1999 (Shimanuki, 1999). He believed that Radio Frequency Identification (RFID) is the base of the internet and the devices that are connected via the internet can be tracked and managed from the computer. A constellation of 27 satellites created by the United States of America provides a highly stable communication system for IoT (Asenjo et al., 2014; Bravo et al., 2014; Carlsson et al., 2016; Ray, 2019). Internet Protocol address (IP address) assigns a label to every device that is connected to the Internet for communication, the introduction of IPv6 changed the course of the address allocation by assigning a 128-bit IP address to every device connected to the internet without any limit. In 2000’s advancement in the IoT helped in developing smart devices like Smart Fridge (LG), Smart Homes, Google self-driving cars, Google Home, Amazon Echo, smart wearable technology, etc., (Breivold & Sandström, 2015; Kumar et al., 2020; Wang et al., 2015)
Figure 1. Development of Internet of Things- Timeline.
The IoT is mainly concentrated in the sectors Consumer, Industrial, Commercial, and Infrastructure varying from Smart Wearables to Smart Homes. Automation helps to fulfill the tasks with minimum human intervention. The third industrial revolution a Digital revolution began with introduction sensors, computers, robots to the industries in the 1970s (King & Mamdani, 1977). The industries are partially automated and are controlled using memory programmable controls and computers without human intervention. The current Industrial revolution Industry 4.0 replaced the third industrial revolution with the advancement in communication and connecting components of machinery, people, sensors, etc., via a wireless network (Chen et al., 2010; O’flaherty, 2005; Stenerson, 2002). Cyber-Physical production systems evolved in Industry 4.0 which enabled controlling and monitoring the production process by computer-based algorithms that helps the machines to learn from the experiences. Advanced technologies Cloud Computing, Industrial IoT, Predictive modeling, etc., overcame the challenges faced due to storage and networking. The data is exchanged between the components of machinery is collected and are applied to computer-based algorithms that use predictive modeling to track and predict the production and helped to increase the production (Bose, 2009; Waller & Fawcett, 2013)
The fourth industrial revolution, Industry 4.0 brought technological changes to production by connecting via a wireless network that connects people and machine components leading to Cyber-physical production systems that convert the factories as Smart factories. Smart Grids, Smart cities, digitally-enabled schools; Drones in military applications are some of the examples. The machines in the smart factories are integrated with technologies like artificial intelligence, Cloud Computing, and helps the machines These technologies removed the barriers of storage and communication, the data is exchanged between different components connected and helps in the prediction of the production. These algorithms use predictive modeling techniques that are designed by the statistic models helps to predict the data (Groover, 2016). For example, Vehicle insurance companies employed sage-based insurance solutions where predictive models utilize telemetry-based data to build a model of predictive risk for claim likelihood. By using the GPS and accelerometer readings one’s black box predicts the risk factors. Advanced driving behavior can be predicted by considering crash records, road history, and user profiles (Jelali, 2012).