• Industrial IoT (IIoT) is defined as a set of tools and applications that allow large companies to create an end-to-end connected environment from the core to the edge. 
  • It also encompasses traditional physical infrastructure like shipping containers and logistics trucks to gather data, react to events, and make smarter decisions with the help of smart devices. 
  • This article explains IIoT architecture and its benefits. 

What Is IIoT?

Industrial IoT (IIoT) is a set of tools and applications that allow large companies to create an end-to-end connected environment from the core to the edge. It also encompasses traditional physical infrastructure like shipping containers and logistics trucks to gather data, react to events, and make smarter decisions with the help of smart devices.

It is an expansion of the internet of things (IoT), which has numerous consumer sector applications. IoT use cases include, for instance, remotely turning off the lights using a smart home device such as Amazon Echo, enabled by Alexa speech recognition.

In industrial operations, this technology is used commercially on a big scale in surroundings with complicated infrastructure and large equipment. In contrast, IIoT enables remote management of the entire factory’s heating, ventilation, and air conditioning (HVAC) systems. This is only one IIoT use case that simplifies and improves enterprise operations management.

How does IIoT work?

IIoT is a subclass of the IoT, wherein companies are redefining how they connect, monitor, analyze, and act on industrial data to reduce costs and promote growth.

General Electric, among the five founders of the Industry IoT Consortium, is credited with coining the phrase “industrial internet.”

The notion behind IIoT is to use the data that “dumb devices” in industrial facilities have been generating for years. Smart machines in assembly lines are not only faster at capturing and analyzing data but also at communicating vital information, which can be useful for making quicker and more precise business decisions.

The integration of information technology (IT) and operational technology (OT) drives IIoT. It is a matrix of networks linking devices and equipment, gathering data via sensor technologies, analyzing it, and integrating it directly into platforms as a service. IIoT will herald a new age of industrial use cases with many opportunities for economic expansion.

IIoT collects a vast amount of field data from the factory floor, transmits it via connection nodes, analyzes it on servers, and transforms the information into actionable insights on a cloud platform. This encourages businesses to make better decisions for their specific markets and target audiences. In other words, IIoT is a system that connects edge devices, such as actuators, sensors, controllers, connection switches, gateways, and industrial personal computers (IPC), to the cloud.

Industry 4.0 and IIoT: How are they related?

Industry 4.0 is the outcome of the fourth industrial revolution. The fourth industrial revolution is defined by the integration of conventional, automated manufacturing with industrial processes powered by intelligent technologies and autonomously communicating devices.

The phrase Industry 4.0, shortened to I4.0 or simply I4, emerged in 2011 from an initiative of the German government that, over the last two decades, advocated the digitization of industrial processes significantly.

As stated by the Boston Consulting Group, IIoT is a major pillar of Industry 4.0, along with additive manufacturing or 3D printing, augmented reality (AR), autonomous robots, big data analytics, cloud computing, cybersecurity, horizontal and vertical system integration, and simulations. This is because autonomous communication among machines and a dispersed digital environment enables the automated resolution of problems that previously required human intervention.

Industry 4.0 covers IIoT, digitalization, and corporate sustainability in its broader scope. IIoT is the driving force behind industry 4.0, which would not exist without it. In other words, IIoT is restricted to data detection, data transfer, data computing, data processing, and domain-specific intelligent applications.

See More: What Is the Internet of Everything? Meaning, Examples, and Uses

IIoT Architecture

A typical industrial IoT architecture or IIoT architecture describes the arrangement of digital systems so that they together provide network and data connectivity between sensors, IoT devices, data storage, and other layers. Therefore, IIoT architecture must have the following:

Components of IIoT Architecture

IIoT Architecture Components

1. IoT-enabled devices at the edge of the network

These are the groupings of networked objects located at the edge of an IoT ecosystem. These are situated as near as feasible to the data source. These are often wireless actuators and sensors in an industrial environment. A processing unit or small computing device and a collection of observing endpoints are present. Edge IoT devices may range from legacy equipment in a brownfield environment to cameras, microphones, sensors, and other meters and monitors.

What occurs at the network’s most remote edge? Sensors acquire data from both the surrounding environment and the items they monitor. Then, they transform the information into metrics and numbers that an IoT platform can analyze and transform into actionable insights. Actuators control the processes occurring in the observed environment. They modify the physical circumstances in which data is produced.

2. Edge data management and initial processing

Without high-quality, high-volume data, sophisticated analytics and artificial intelligence cannot be used to their full potential. Even on the sensor level, data processing is possible, which is necessary if you need information immediately.

In this aspect, edge computing provides the quickest answers since data is preprocessed at the network’s edge, at the sensors themselves. Here, you can conduct analyses on your digital and aggregated data. Once the relevant insights have been gathered, one can move forward to the next stage instead of sending all the collected information. This additional processing decreases data volumes sent to data centers or the cloud.

3. Cloud for advanced processing

Edge devices are restricted in their capacity for preprocessing. While you should strive to reach as near to the edge as is realistically possible to limit the consumption of native computational power, users will need to utilize the cloud for processing that is more in-depth and thorough.

At this point, you must choose whether to prioritize the agility and immediacy of edge devices or the advanced insights of cloud computing. Cloud-based solutions can perform extensive processing. Here, it is possible to aggregate data from different sources and provide insights that are unavailable at the edge.

In the context of IIoT architecture, the cloud will have:

  • A hub: It offers a secure link to the on-site system in addition to telemetry and device control. The hub provides remote connectivity to and from on-premises systems, if required, across several locations. It maintains all elements of communication, such as connection management, the secure communication channel, and device verification and authorization.
  • Storage: It is useful for storing information before and after it is processed.
  • Analytics: It aids in data processing and analysis.
  • A user interface: It provides visualization for conveying the analysis findings to the end user, often via a web browser interface and also through alerts via email, text message, and/or phone call.

4. Internet gateways

Here sensor data is gathered and turned into digital channels for further processing at the internet gateway. After obtaining the aggregated and digitized data, the gateway transmits it over the internet so that it may be further processed before being uploaded to the cloud. Gateways continue to be part of the edge’s data-collecting systems. They remain adjacent to the actuators and sensors and perform preliminary data processing at the edge.

Gateways may be deployed as hardware or software:

  • Hardware: Hardware gateways are autonomous devices. Wire-based (analog and digital) and wireless interfaces are provided for the downstream sensor connection. They also provide Internet connectivity, either natively or via a standard link to a router.
  • Software: On PCs, software gateways may be installed instead of connecting hardware gateways. The software operates either in the background or foreground and offers upstream and downstream communications links as the hardware entry point, with the PC supplying the physical interfaces. Software-based gateways may enable access to visual sensor settings and sensor data presentation via user interfaces.

5. Connectivity protocols

Protocols are required for the transfer of data across the IIoT system. These protocols should preferably be industry-standard, well-defined, and secure. Protocol specifications may contain physical properties of connections and cabling, the procedure for establishing a communication channel, and the format of the data sent over that channel.

Some of the common protocols used in IIoT architecture include:

  • Advanced Message Queueing Protocol (AMQP): It is a connection-led, bidirectional, multiplexing, compact data-encoding message transport protocol. AMQP, unlike HTTP, was built for IIoT-oriented cloud connectivity.
  • MQ Telemetry Transport (MQTT): This is a compact client-server message transport protocol. MQTT benefits IIoT devices because of its short message frame sizes and minimal code space.
  • Constrained Application Protocol (CoAP): This is a datagram-led protocol that may be deployed via a transport layer, including user datagram protocol (UDP). CoAP is a condensed version of HTTP developed for IIoT requirements.

6. IIoT platforms

IIoT systems are now capable of orchestrating, monitoring, and controlling operations throughout the whole value chain. The platforms control the device data and manage the analytics, data visualization, and artificial intelligence (AI) duties from the edge devices and, in certain cases, the sensors right through to the cloud and back.

The industrial internet reference architecture (IIRA) may serve as a reference for developing sophisticated systems in the IIoT domain. In general, the IIRA’s frameworks advocate that businesses design a framework using a systematic approach, which includes feedback and iterations. In addition, the report suggests customizing IIoT designs for a particular business sector, such as energy, healthcare, transportation, and governmental use.

See More: Top 10 Applications of IoT in 2022

Benefits of IIoT

Benefits of IIoT

Benefits of IIoT

Industrial IoT offers the following benefits:

1. Boosts efficiency

The biggest benefit of IIoT is its ability to help enterprises automate and thereby maximize operational efficiency. In addition, physical equipment may be linked to software solutions through sensors that continuously monitor performance. This provides enterprises with a greater understanding of the operational efficiency of specific pieces of equipment and whole fleets. Additionally, IIoT enables data-driven decisions and remote monitoring of all production processes.

2. Increases production

By boosting equipment usage, organizations with IoT-enabled manufacturing processes are likely to increase their productivity. As previously mentioned, networked devices deliver a continuous stream of data that offers insights into equipment operation. This allows you to increase the total equipment effectiveness, maximizing machine performance during their operational time. Additionally, using IIoT devices improves human capital usage. Smart devices can be utilized to perform menial, repetitive, and hazardous activities, thereby freeing employees for other, more strategic production-related jobs. 

3. Reduces errors

The use of IIoT compels organizations to automate production operations. Eliminating the human element from industrial operations removes inefficiencies that would result in defective products exiting the assembly line. With fewer quality flaws, the company’s profitability increases due to improved customer satisfaction and brand recognition.

See More: What Is IoT Device Management? Definition, Key Features, and Software

4. Predicts maintenance needs

Predictive maintenance is a strategy for avoiding asset failure via the analysis of production data to discover patterns and forecast impending problems. 

Incorporating IIoT sensors into industrial equipment allows notifications for condition-based management. These sensors record the temperature, humidity, and other ambient variables in the working area, as well as the composition of the materials and the impact that transportation factors have had or may have on the shipment. All of this data is useful for predictive maintenance. Consequently, you may avoid asset failure, decrease expenses, and minimize machine downtime.

5. Keeps workers safe

Smart manufacturing enables greater security, with all IIoT sensors collaborating to monitor employee and workplace safety. Integrated safety systems may safeguard work floors, production lines, and personnel. In the event of an accident, the whole facility may be notified, activities can be halted, and senior management can intercede to address the situation. This incident may also yield useful information that can be used to avoid future occurrences.

6. Saves energy costs

Industrial operations are responsible for significant worldwide supplied power, which is detrimental to sustainability and the overall bottom line. Constant monitoring of your system using sensors and gadgets might reveal inefficiencies that lead to waste. This encompasses not just monitoring your equipment but also your comprehensive business, such as regulating the temperature, water use, humidity, and lighting of your facility. In addition, as IoT technology advances, sensors consume less energy, which is a boon to your bottom line.

7. Improves field services and customer experience

IIoT can help improve the delivery of field services. It is determined by aspects such as time, context, and technical personnel participation in a specific service operation. IIoT also allows real-time data visibility. This implies that the original equipment manufacturer (OEM), the end consumer, and any other interested parties are informed of the risks and difficulties as they arise so that it results in a positive experience.

See More: Distributed Computing vs. Grid Computing: 10 Key Comparisons

IIoT Examples

Most notable industries and companies, from retail to manufacturing, use IIoT in some way. Here are some notable IIoT examples that have resulted in positive business outcomes:

1. PepsiCo uses IIoT for asset tracking

Embedded IIoT components in shipping, fleets, and packaging may aid in tracking inventories from start to end. It should also maintain an equilibrium between supply and demand by tracking inventory levels. PepsiCo is an example of an organization that utilizes this industrial IoT use case. It employs a vast array of technologies to adapt to market demands, manage inventory system visibility, and automatically adjust replenishment rules.

2. BMW uses IIoT to create digital twins of its products

Digital twins are an industrial IoT application in which a sophisticated collection of sensors are utilized to construct an accurate simulation of a product or production environment, down to the last detail and physical characteristics. BMW employs IIoT, artificial intelligence (AI), and immersive technologies to construct a digital duplicate of a factory’s entire production process. This enables the organization to develop, evaluate, and optimize goods in a realistic setting without incurring related expenses or risks.

3. L&T uses IIoT for remote monitoring and cost savings

The energy and utilities sector utilizes large operational infrastructure, sometimes in hazardous conditions where human operators are unsuitable. In these instances, IIoT devices may gather and transmit crucial operational data without the presence of a human operator. For instance, Larsen & Toubro (L&T) is deploying a remotely monitored Green Hydrogen Station in Gujarat, India. Using IIoT, L&T may reduce operational and energy expenses and gain relevant insights into the functioning of the energy plant.

4. An Irish distillery using IIoT for environmental monitoring

The food and beverage sector relies heavily on the capacity to manufacture and store products under ideal environmental conditions. Industrial IoT systems may monitor environmental changes to warn floor managers before product degradation occurs. The distilleries producing alcoholic beverages are an ideal example of IIoT since they operate under delicate environmental conditions. Frilli, a supplier of distillation plants, has recently deployed IIoT technologies for an Irish beverage brand to provide automation, efficiency, and uniform process flows.

5. Airbus uses Bosch’s IIoT platform to build a smart factory

Airbus seeks to eliminate faults by integrating industrial IoT sensors into machines and equipment on the manufacturing floor and providing employees with wearables (such as industrial smart glasses). A single error in the process might cost the organization millions of dollars to rectify. After launching its “Factory of the Future” in collaboration with Bosch, Airbus is using digital intelligence to optimize operations and increase productivity.

See More: What Is the Internet of Everything? Meaning, Examples, and Uses


Industrial IoT is now a staple for large companies and among the key products offered by major cloud vendors like Microsoft and Amazon Web Services (AWS). IIoT extends the capabilities of advanced data analytics and the cloud to industrial applications such as equipment maintenance, factory operations, supply chain management, and personnel safety. The data from IIoT platforms can even help simulate and test products in a digital environment to perfectly converge digital with physical systems, exponentially improving industrial outcomes.

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