Value Of Industrial Internet Of Things (IIoT)

Industrial firms across the world are realizing the value of digital transformation in terms of potential sales and strategic positioning. A significant transition is underway toward more service-oriented solutions that leverage the pervasive connectivity enabled by the Industrial Internet of Things (IIoT). The Industrial Internet of things a.k.a. “IIoT” can be applied to a wide variety of industries such as logistics development, oil and gas, transportation, energy/utilities, mining and metals, aviation and other critical industrial sectors.

Like the Internet of Things in general, the Industrial Internet of Things opens up many possibilities in automation, optimization, smart manufacturing, asset performance management, maintenance, and industrial regulation. The more mature aim of industrial digital transformation via IIoT is to provide new ways of serving customers and to create new business models.

Global Significance

IIoT enables businesses and organizations to have greater productivity and reliability in their activities, emphasizing machine-to-machine (M2M) communication, big data, and machine learning. IIoT includes industrial applications, including robots, medical devices, and production processes identified by the software.

IIoT goes beyond the usual physical consumer devices and inter-networking commonly associated with the IoT. The convergence of information technology (IT and operational technology ‘OT’) is what makes it distinct. OT relates to the networking of industrial control systems (ICSs) and operating processes, including human-machine interfaces (HMIs), data acquisition and supervisory control (SCADA) systems, distributed control systems (DCSs), and programmable logic controllers (PLCs).

Overarching Solution

There are several names for this overarching idea, but the Internet of Things (IoT) is the most well-known over the past decade. Smart houses, mobile exercise equipment, and wired toys are the main fields of IoT. The Industrial Internet of Things (IIoT) subset includes smart agriculture, smart cities, smart factories, and the intelligent (utility) grid.

With reduced system downtime, more generous storage, and remote asset monitoring, the move towards Industry 4.0 has allowed industrial users to use data and analytics for predictive analysis. Despite the hype, IIoT still has its own set of unique challenges that businesses need to tackle in the future to reap all its benefits.

There are three distinct challenges IIoT faces: First, far too many organizations are either siloed or fractured. Preventing achievement of true end-to-end processes and synergies in the development of innovative products and services that cover anything from production to consumer use. Second, corporate mindsets are too product-focused and not consumer-focused enough; future markets will need them to be much more attentive to customer needs. And finally, in product incubation and consumer analytics, there is a skills gap. In a changing industrial landscape, skillsets honed for conventional manufacturing aren’t always well suited to maximizing customer analytics or incubating new value for the company. The integration of IIoT calls for a new generation of operators familiar with forward looking technologies and processes.

Present Solutions

Producers of consumer IoT devices have been promoting the advantages of smart connected home appliances for years, such as smart thermostats and smart refrigerators. Consumer IoT applications such as these have caught the attention of public interest, but the story is a lot bigger than just smart appliances.

Connected devices have more significant potential, so more attention is being diverted to smart warehouses, industrial automation, connected logistics, and various other business use cases instead of intelligent home security systems and smart thermostats.

Scalability, real-time capability, interoperability, data security and safety are critical criteria for an IIoT architecture. A central role is played by sensors, actuators, and intelligent devices that collect (edge computing) data and send it to (network) servers. They are further processed at the cloud computing level into action-relevant “smart data” using intelligent algorithms. This then forms the base of automated procedures. IoT systems that enable the creation and administration of IIoT applications are now offered by major cloud providers such as Microsoft, Amazon Web Services, and Google. These solutions are particularly suitable for entry-level.

Relevant Trends

It will help shape the future if industrial organizations play a constructive role, bringing goods to the market that meet the current demands and are not shocked by destructive changes. Industrial businesses must make a diligent and deliberate shift to new market and operating models that will produce the future’s service-oriented, customer-centric, IIoT-based goods. However, the challenge is they must do so while still maintaining the success of their traditional core businesses. This deliberate pivot is all about transforming and increasing the core business while balancing human and machine resources to cut operating costs and free up investment potential in a sustainable manner; carefully allocating investment capital to spur new development and scale new products and services that will ensure long-term success.

Data analytics and the prioritization of innovation management is the key. Today, the future’s potential has to be recognized, and the solutions that will be needed tomorrow have to be created. This includes robust, well-founded data on potential patterns, future innovations, and their impacts.

Global Implications

The automotive industry holds a large share of investment and market share among the sectors, with both discrete and process manufacturing investing heavily in IIoT adoption. Besides, industry management is keen on IIoT adoption; 87 percent of the decision-makers in the manufacturing industry favored adoption with industrial automation, quality & enforcement, production planning & scheduling, supply chain and logistics, and plant safety & protection as the primary use cases, according to a recent study by Microsoft.

With the emergence of Industry 4.0, both discrete manufacturing and process manufacturing are gaining momentum in IIoT as IIoT provides ways to maximize operations, minimize downtime, improve performance and help make data-driven decisions, raising profit margins and lowering costs.

The backbone of IIoT is networking technologies, especially wireless technology. Numerous devices and sensor nodes are connected to the Internet to allow machine-to-machine communication using these technologies. These technologies also allow large amounts of data to be collected for enhanced decision-making. An extensive range of wireless communication technologies is available based on connectivity range, power requirements, and data transfer rates. For machine-to-machine connectivity, the industrial sector is increasingly relying on cellular technologies.

During the forecast era, the market for farm management software is expected to rise at the highest growth rate. The growth of farm management systems is expected to be driven by the growing global trend of precision farming adoption. Precision farming allows farmers to make decisions that can not be analyzed and interpreted without using appropriate tools due to the lack of data collected. Farm management systems software enables farmers to use the data gathered over the years to produce formula-based predictions, evaluate average yield data, generate benefit maps, and test results for importing soil. The overall trend of leveraging big data for operational efficiency purposes has had strong growth over the past couple decades, but will skyrocket with the new wave of data coming in from IIoT connected devices and equipment; precision farming is just one example of what is to come in the future with the emergence of IIoT.