What is the Industrial Internet of Things (IIoT)?

The industrial internet of things (IIoT) – also known as Industry 4.0 – is radically altering how businesses, particularly industrial firms, operate. As businesses digitally transform, a chasm forms between their physical and digital assets. 

 

The link between the two is provided by industrial IoT. If a physical object is connected to the Internet, it can be transformed into an IoT device. This generates a large amount of data that can be used to improve performance, make better decisions, and boost innovation. 

Industrial automation and productivity enhancements can be achieved through the use of IoT by maximizing previously underutilized assets and operational data.

 

 

What is IIoT?

 

The use of smart sensors and actuators to improve manufacturing and industrial processes is referred to as the industrial internet of things (IIoT). 

 

IIoT, also known as the industrial internet or Industry 4.0, leverages the power of smart machines and real-time analytics to capitalize on data produced by "dumb machines" in industrial settings for years. 

 

The driving philosophy behind IIoT is that smart machines are not only better than humans at capturing and analyzing data in real-time, but they are also better at communicating important information that can be used to drive faster and more accurate business decisions.

 

Connected sensors and actuators allow businesses to detect inefficiencies and problems earlier, saving time and money while supporting business intelligence efforts. 

 

In particular, IIoT has enormous potential in manufacturing for quality control, sustainable and green practices, supply chain traceability, and overall supply chain efficiency. IIoT is critical to industrial processes such as predictive maintenance (PdM), enhanced field service, energy management, and asset tracking.

 

How does IIoT Work?

 

Typical IIoT systems necessitate data sharing between multiple devices and networks, from the edge (sensors, remote devices, and computers) to the cloud (centralized computer systems). 

 

This is difficult because the sheer volume of data, let alone the stringent safety and security requirements, can easily overwhelm a network, especially one that spans remote operations. These interconnected systems necessitate novel approaches to managing increased data volume, performance demands, security risks, and safety certifications.

 

Managing IIoT data flow is critical to ensuring that IIoT applications function as intended. The data bus is a tried-and-true architecture proposed by the Industrial Internet Consortium. The databus manages data in motion, as opposed to a database, which manages historical data at rest.

A data bus is a data-centric software framework that distributes and manages real-time data in the IIoT, allowing applications and devices to function as a single integrated system. 

 

The data bus makes application and integration logic easier to understand. Software components communicate via shared and filtered data objects rather than messages. Applications read and write the values of these cached data objects directly.

 

Also Read | IoT in Energy Sector

 

Applications of IIoT

 

The Internet of Things is a game-changer for any manufacturing industry that produces physical products or manages product transportation. IIoT can improve operational efficiencies, paving the way for the development of entirely new business models. There are a wide range of applications of IIoT in a variety of industries. 

 

1. Production

 

Currently, the manufacturing sector is the most reliant on IIoT technology. Smart machines with IIoT capabilities can self-monitor and anticipate potential production issues. As a result, downtime is reduced and efficiency is improved.

 

2. The Supply Chain

 

While maintaining production numbers is critical, ensuring smooth delivery throughout the supply chain is also critical. Orders can be automatically replenished with IIoT when necessary. 

 

This reduces waste, keeps stock numbers stable, and ensures that the right amount of raw materials is always available. Employees can focus on more complex areas of function with the automation of supply chains and ordering.

 

3. Building Administration

 

The majority of building management issues can be addressed by IIoT technology. Sensor-driven climate control eliminates all uncertainty associated with managing a building's internal climate and takes into account all necessary factors such as the number of people, ventilation spots, machinery, and more. With smart devices that assess potential threats from any building entry point, IIoT improves building security.

 

4. Healthcare

 

Smart devices have long been used in healthcare. Healthcare professionals can remotely monitor patients and receive notifications when their status changes. 

 

This improves the precision and personalization of healthcare. Artificial intelligence may be able to assist doctors with diagnoses in the future, allowing them to treat patients more accurately and effectively.

 

5. Retail

 

In retail, IIoT technology enables quick marketing decisions tailored to each location. Companies can update storefronts based on consumer interests in specific regions, and they can target audiences with smarter promotions. These data-driven insights help a store stand out from the crowd.

 

Sensors are not a new technology; companies have used them for years to track goods or monitor machines. The difference in IIoT is the ability to implement these changes on a larger scale as sensor costs, comprehensive wiring networks, and big data analytics have decreased.

 

Advantages of the Industrial Internet of Things

 

As IIoT devices become smaller, cheaper, and smarter, they will be able to be used almost anywhere. The data they generate can be turned into actionable insight, resulting in incredible business IIoT benefits such as:

 

1. Increased Operational Effectiveness

 

Industrial IoT software enables you to build environments of connected assets that provide numerous operational efficiency benefits. Sensors in production systems, assembly lines, warehouses, and vehicles generate data that allows managers to monitor how an asset is performing and address problems before they occur.

 

2. Productivity has increased

 

Industrial IoT solutions provide real-time data on equipment and human performance to help streamline and improve business processes and workflows.

 

3. Cost-cutting

 

IIoT deployment provides significant cost savings for organizations. According to some estimates, industrial IoT devices can save as much as 70% on lighting and 30% on air conditioning.

 

4. Improved Customer Service

 

Manufacturers can capture and analyze data on how customers use their products by embedding industrial IoT sensors into them, allowing them to improve future product upgrades and releases.

 

5. Cut back on Waste

 

One of the most important advantages of IIoT software is inventory management. By attaching IIoT devices to products, warehouses, and vehicles, you can improve the efficiency of the entire supply chain process, reducing the need for excess inventory and the risk of stock-outs.

 

6. New Business Models

 

Industrial IoT technologies lay the groundwork for delivering new, innovative, and data-driven business models. Manufacturers, for example, can use industrial IIoT data from sensors on their products to provide associated services such as remote diagnostics or predictive maintenance.

 

Also Read | 8 Applications of IoT in Daily Life

 

Challenges associated with IIoT

 

Here are some of the most important industrial IoT challenges that businesses should be aware of:

 

1. A Costly Investment

 

The high cost of adoption is one of the more obvious industrial IoT challenges. True, one of the main promises of IoT is that it will reduce costs through improved asset management, access to business intelligence, and productivity gains.

 

However, it is difficult for organizations to justify the cost when A: they are unsure of the expected ROI and B: they have no experience implementing connected systems. According to Microsoft's 2019 IoT Signals report, one of the top reasons for delaying IoT adoption was a lack of resources, cited by 29 percent of organizations.

 

2. Secure data storage and management

 

IoT devices generate a TON of data. According to an IDC white paper published in 2018, there will be 160 zettabytes of data generated globally by 2025 (10 times the amount generated at the time of the report), owing in part to the increased adoption of industrial-grade IoT devices.

 

The issue here is that this massive amount of data must be processed extremely quickly in order to detect patterns in real-time. Given the level of security that IIoT technologies necessitate, organizations must devise a strategy for streamlining data monitoring, management, and storage, allowing for rapid response times to incoming threats.

 

It's also worth noting that introducing all of these new sensors, devices, and software may introduce new types of data that an organization isn't yet equipped to handle.

 

Another significant IIoT challenge is that even if an organization implements all of the necessary sensors, software, and equipment, the ROI can only be realized if the organization has both the necessary tools and expertise.

 

3. Outages in Connectivity

 

One of the most important considerations for enterprises before embarking on the big IIoT transformation is the requirement for constant, uninterrupted connectivity.

 

Even if you only talk about uninterrupted internet uptime, achieving 100 percent availability is nearly impossible. Whether it's due to maintenance or something else, the connection may be lost at some point.

 

As a result, in order to avoid downtime, organizations will need to find a suitable vendor for meeting connectivity requirements. Regrettably, requirements differ by industry. Organizations must consider range, location (i.e., connectivity between multiple job sites/factories), and power consumption.

 

For example, cellular connectivity may be a good option if your system requires a lot of bandwidth, whereas a low-power long-range solution may be your best bet for monitoring assets for years at a time.

 

Outages in IIoT introduce several risk factors that go far beyond the annoyance of a temporary WiFi outage. When sensors are used to detect hazards such as gas leaks, an outage could be a matter of life and death. Outages on smart grids can knock out power for an entire community.

 

4. Integrating Legacy and IIoT Infrastructure

 

The more complex your IIoT system is, the more likely it is that your IT admins and OT engineers have visibility, access, and control over every moving piece in the ecosystem.

 

As organizations deploy IIoT devices on legacy equipment and various devices made by different companies, it becomes extremely difficult for employees to monitor and control the end-to-end operation.

 

As of now, there is no set of standards for how organizations should process data between various devices and machines. There is no standard for ensuring interoperability or securing a system that includes equipment that was never intended to be "smart" in the first place. 

 

While IT professionals can collaborate with operations teams and leadership to apply the same standards they've long used to ensure hardware security and function, it's not an easy process–especially given that no two systems look the same.
 

Also Read | IoT in Manufacturing

 

 

Difference between IoT vs IIoT

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IoT vs IIoT

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IIoT	IoT
It is primarily used in industrial applications such as manufacturing, power plants, oil and gas, and so on.	It focuses on general applications such as wearables, robots, and machines.
It employs critical equipment and devices linked via a network, the failure of which could result in a life-threatening or other emergency situation, necessitating the use of more sensitive and precise sensors.	Its implementation begins on a small scale, so there is no need to be concerned about life-threatening situations.
SSL encryption, in-transfer data encryption, at-rest data encryption, visual monitoring of servers, closed-loop systems, and biometric login are all required for IIoT infrastructure.	IoT, on the other hand, necessitates less strenuous network security to keep consumers' data out of the public domain. Data privacy is currently the most critical Internet of Things (IoT) security issue.
Processing very large amounts of data on an industrial scale.	Handling volumes ranging from very small, such as wearable devices, to objects you use every day, such as thermostats, irrigation pumps, kitchen appliances, and Internet-connected televisions.
It can be programmed remotely, allowing for on-site programming from a distance.	It allows for simple off-site programming.
It is primarily used in industrial applications such as manufacturing, power plants, oil and gas, and so on.	It focuses on general applications such as wearables, robots, and machines.

 

IIoT devices will play a significant role in digital transformation, particularly as organizations attempt to digitize their production lines and supply chains. Furthermore, big data analytics will evolve to incorporate IIoT data.