In the industrial Internet of things (IIoT), connected devices, such as sensors, instruments, and other devices, are networked with computers’ industrial applications, such as manufacturing and energy management, to form a network of connected appliances. Data can be collected, exchanged, and analyzed through this connectivity, potentially improving productivity and efficiency. Using cloud computing to refine and optimize process controls, the IIoT is an evolution of a distributed control system (DCS).
The Overview
IIoT technologies include cybersecurity, cloud computing, edge computing, mobile technologies, 3D printing, robotics, big data, cyber-physical systems, and RFID technology. The following are five of the most important ones that should be mentioned:
- The Cyber-Physical System (CPS) is the platform on which the Internet of Things (IoT) and the Industrial Internet of Things (IIoT) run, and therefore is the key to the connecting of previously disconnected physical machines. Using CPS, the dynamics of the biological process can be integrated with the dynamics of software and communication, providing abstractions and tools for modeling, designing, and analyzing the physical process.
- As opposed to having a direct connection to a server, cloud computing allows IT services and resources to be uploaded and retrieved from the Internet instead of communicating with it directly. You can keep your files on cloud-based storage systems rather than on local storage devices by using cloud-based storage systems.
- A distributed computing paradigm called edge computing is characterized by its ability to bring computer data storage closer to where it is needed. The concept of edge computing is different from cloud computing in that it refers to the decentralized processing of data at the edge of a network. For the industrial Internet to succeed, it will require an architecture that incorporates edge-plus-cloud technology rather than just a centralized cloud to transform productivity, products, and services in the industrial field. Read More
- An application of big data analytics involves the analysis of large and varied data sets, or big data, to make business decisions.
- AI: Artificial Intelligence (AI) is the creation of intelligent machines that act and react like humans. Using machine learning, the software can predict outcomes without explicitly being programmed.
A security system
During the expansion of IIoT, new security concerns arise along with it. Whenever a new device or component is connected to the IIoT, there is a potential for liability to arise. The Internet of Things will account for more than 25% of recognized attacks on enterprises by 2020. Cybersecurity measures for internet-connected devices are vastly inferior to those for traditional computers, which allows botnets like Mirai to hijack them for DDoS-based attacks. It is also possible to infect industrial controllers connected to the Internet, as in Stuxnet. Click Here
IIoT-enabled devices can also allow for more “traditional” forms of cybercrime, such as the 2013 Target data breach, in which hackers accessed Target’s networks via credentials stolen from a third-party HVAC vendor. As a result of security concerns, the pharmaceutical manufacturing industry needs to be faster to adopt IIoT. Hardware fragmentation is a challenge in providing security solutions for IIoT applications. Consequently, security architectures are becoming software-based or device-agnostic. When connecting critical infrastructure, hardware-based approaches are often used.
A Brief History
The programmable logic controller (PLC) was invented in 1968 by Richard E. Morley. General Motors used to manufacture automatic transmissions for their vehicles. They allowed fine control of individual manufacturing elements. Yokogawa and Honeywell introduced the first DCSs in 1975, the TDC 2000 and CENTUM systems. DCSs allowed flexible process control throughout a plant, with the added benefit of redundancy through distributing power across the entire system, eliminating a central point of failure.
Carnegie Mellon University created the first internet-connected appliance in 1982 to report its inventory and whether newly loaded drinks were cold. People began exploring the concept of an intelligent network of devices. In IEEE Spectrum in 1994, Reza Raji described the idea as “moving small packets of data to a large set of nodes Automate everything from appliances to factories.”
After cloud technology emerged in 2002, which enabled data storage for historical analysis, 2006 was when the OPC Unified Architecture was developed, allowing remote communication between devices, programs, and data sources without human intervention.
Utilizing the industrial Internet of things (by equipping objects with sensors) is one way to achieve this goal microchips capable of identifying them) would create instant and ceaseless inventory control. Another benefit of IoT systems is the ability to create a digital twin. Using a digital twin allows you to experiment. Integrating new cloud data without stopping production or interrupting operations to compromise safety is possible since you can refine the new processes virtually until they are ready for implementation. New employees don’t have to worry about real impacts on the live system when they train on a digital twin.
Frameworks & Standards
In addition to supporting the interaction between “things,” IoT frameworks facilitate the development of distributed applications and distributed computing.
- Cognitive IoT combines traditional IoT with machine Natural language processing, learning, and contextual information. Chatty Things is a fully open, vendor-independent standard based on XMPP that provides distributed, scalable, and secure infrastructure using XMPP.
- The REST architecture allows things to communicate over Hypertext Transfer Protocol and is quickly adopted for IoT applications as it will enable communication between things and central servers.
- On top of TCP/IP, MQTT is a publish-subscribe network architecture that enables bi-directional communication between a thing and a broker that uses a publish-subscribe mechanism.
- IBM’s Node-RED is an open-source project designed to connect APIs, hardware, and online services.
- There are several standards designed by the OPC Foundation to connect computer systems with automated devices.
- The OMG Data Distribution Service (DDS) is an open international middleware standard to deliver publish-subscribe communications for real-time and embedded systems.
- Industrialization is essential to note Internet Consortium’s concepts of Industrial Internet Reference Architecture (IIRA) and German Industry 4.0 define a standard for IIoT-enabled facilities under the Industrial Internet Consortium (IIC).
Industries & Applications
In the manufacturing industry, the industrial Internet of things refers to the industrial subset of IoT. Improved productivity, analytics, and workplace transformation are potential benefits of the industrial Internet. By 2030, IIoT is predicted to generate $15 trillion of global GDP.
The IoT is not just about connectivity and data acquisition. They are not the end goal but the foundation. There are many technologies out there, but predictive maintenance is one of the easiest to use because it applies to existing assets and management systems and is a more straightforward application. By implementing intelligent maintenance systems, you can reduce downtime and increase productivity, thus saving up to 12% on scheduled repairs. The cyber-physical system (CPS) is the core technology of big industrial data and is an interface between humans and the cyber world, which will reduce overall maintenance costs by 30%.
Among the real-world applications of intelligent LEDs include directing shoppers to vacant parking spaces or highlighting changing traffic patterns, detecting leaks on water purifiers and alerting managers via computer or smartphone, tracking personnel and ensuring their safety with RFID tags attached to safety gear, tracking personnel and ensuring their safety with RFID tags attached to safety gear, and collecting data from multiple systems to simulate new processes by embedding computers within power tools that record and track torque levels of each tightening.