Overview of the Industrial Internet of Things

Fifty years ago, when we thought of futuristic industrial technology, we envisioned agile, human-like robots. While robotics have advanced, the real breakthrough is connectivity. The Industrial Internet of Things (IIoT) connects machines, people, and systems in real time, enabling them to share data and integrate with central business platforms.

IIoT creates an AI-powered “system of systems” that can curate, manage, and analyse data from one end of the business to the other. Within this system, machines, people, and other systems can work together in real time, powering more resilient operations and sustainable business growth.

IIoT definition

IIoT stands for the Industrial Internet of Things—and as the name suggests it refers to the use of Internet of Things technology that connects machines, devices, and sensors, in industrial applications. When operated by a modern ERP with AI and machine learning capabilities, the data generated by IIoT devices can be analysed and utilised to improve efficiency, productivity, visibility, and more. IIoT networks typically support machine-to-machine (M2M) communication and the regular transmission of data between the central system and all IIoT-integrated devices. IIoT technology is also a fundamental component of Industry 4.0 technologies.

IIoT vs IoT

The differences between these technologies lie less in how they work and more in how they are used. The majority of the world’s IoT solutions tend to have individuals as their end users and are most commonly incorporated into items such as smart watches, voice-controlled digital assistants, or smart appliances and televisions.

IIoT is a subset of IoT, and, while it is driven by the same basic technologies, its focus is much more on automation and efficiency across an entire, connected organisational ecosystem—as opposed to an isolated user. In IIoT networks, gathering and curating data is only the first step in a more complex process. To provide maximum benefit to a business, artificial intelligence and machine learning must be applied to that data to deliver accurate insights and to optimise workflows and automated tasks. Human users must also be able to interact with these devices as seamlessly as possible to create cyber-physical networks in which the best of human and technological abilities can augment each other.

How it works: IIoT technology

For an IIoT network to be effective, it must do two essential things: connect devices and assets to each other and a central system; and make it possible for the data they gather and transmit to be stored, managed, analysed, and put to good use.

To do so, IIoT networks rely on the following technologies:

• Connectivity (and 5G): IIoT networks require the capacity to send and receive the vast volumes of data generated by machines and devices. This has traditionally been both enabled and limited by the power of Wi-Fi connectivity. However, 5G and other advances in mobile networks are changing this calculation, increasing bandwidth to handle larger data sets, while also reducing latency and power consumption. These characteristics can support a greater number of devices capable of sending and receiving signals more quickly for more efficient data processing and longer battery life.
• IIoT sensors: Today, sensors are typically built into new industrial equipment and machinery.  But analogue machinery and manufacturing equipment can also be fitted with IoT gateway devices such as cameras and gauges. This enables IIoT assets to detect conditions in their environment, including the proximity of other objects, air pressure or humidity—as well as motor speed, fluid levels, and other mechanical conditions. All of this information can then be processed locally to inform real-time actions or be transmitted to a central system (such as an ERP) via the cloud for advanced analysis.
• Cloud computing power and edge computing: Both cloud and edge computing technologies have greatly improved the flexibility and usability of IIoT. Via the cloud, IIoT networks can utilise a high degree of processing power and storage capacity on demand. This means that devices within the network can gather and transmit larger and more complex data sets. Edge computing simply means taking systems that can process and analyse that data and bringing them on-premises—physically closer to the IIoT network. This helps reduce latency and delays and allows time-sensitive IIoT data to be processed in real time. For more in-depth, less urgent analysis, IIoT data can be periodically sent to the central, AI-powered system.
• AI and machine learning: Artificial intelligence and machine learning technologies enable businesses to process IIoT data using advanced and predictive analytics. Modern databases and machine learning algorithms also help businesses to manage and make sense of diverse data sets and unstructured and complex data. With these tools, IIoT data can be analysed in almost limitless combinations with other types of data insights such as customer feedback, weather reports, marketing analytics, and more. As systems learn over time and as data sets become larger and more precise, companies can begin to gather increasingly complex and sophisticated insights and learnings to help them compete, save money, and meet customer demands.
• Security for cyber-physical systems: The same interconnectedness that gives life to IIoT networks also puts them at risk. While most companies have strict security and access protocols around their central systems and databases, their IoT devices are sometimes relatively unprotected. Essentially, they can act as basement windows, giving full access to a system that is otherwise fairly secure via its conventional entry points. Fortunately, security protocols and technologies are largely keeping pace with IIoT advancements. What often lags behind, however, are cross-business security protocols that are clearly communicated and reinforced to every employee and operator. If they are not already, security strategies must become a top priority for any modern business.

Top six benefits of IIoT and cyber-physical systems

As part of an overall process of digital transformation, an IIoT network provides a powerful tool for building greater resilience and competitiveness.

1. Enhanced business agility: When IIoT devices share data in real time, they contribute to an intelligence network that continually gathers, analyses, and learns from data. This enables businesses to respond to opportunity—and risk—with speed and decisiveness. And those same devices not only send data but can also receive instructions based on data analysis to adapt and optimise their automated workflows.
2. Healthier machines: Devices and machines in an IoT network are continually transmitting operational logs and performance data. AI and machine learning algorithms use this sensor data to gain valuable insights into predictive and other maintenance requirements, which can lead to significant cost savings.
3. Greater efficiency: Unfortunately, “if it ain’t broke” is often the stance that businesses take when prioritising their operational needs. This attitude can lead to inefficient legacy processes lingering beyond their prime. The application of advanced analytics to IIoT data leads to ongoing recommendations and strategies for updating processes, streamlining workflows, and achieving increased efficiency and productivity.
4. Smarter inventory management: Today’s customers want next-day delivery and ever-increasing variety and customisation. This means a larger network of smaller, more distributed warehouses and a broader inventory with more individual items. IIoT devices can help to connect all these geographically dispersed warehouses, inventories, and delivery networks—giving supply chain managers (and customers) a real-time idea of where inventories are at all times. And for some products, devices, such as additive (3D) printers, can reduce dependence on remote manufacturers, allowing businesses to maintain virtual inventories and manufacture the products they need—on demand and on site.
5. Safer workers:  In any industrial setting, there is always the risk of injury or strain. Today, many businesses are reducing this risk with the use of IoT workplace safety devices. These may deliver warnings via wearable sensors or use VR headsets to help workers merge their sensory experiences with the precision of smart devices and machines. In manufacturing settings, IIoT devices can also be fitted with sensors to monitor physical interaction with their human counterparts to help protect them from unexpected risk or repetitive strain—and even to inform new, safer workflows over time.
6. Improved customer service: IIoT networks connect more than just the devices and machines within a business—they also integrate customer experience and feedback.  This integration results in more seamless shopping experiences, more transparent and personalised logistics, and greater ability to incorporate customer feedback and preferences into the manufacturing and development of new products. Real-time and meaningful engagement with customers leads to a more competitive and resilient business model.

Industrial IoT applications and examples

With its ability to monitor and report on conditions on the ground in real time, IIoT technology has broad applications across modern industry sectors—especially when integrated with AI-powered analytics, automated processes, and a best-in-class ERP system.

• Smart manufacturing: Businesses gather data from customer feedback, media trends, and the global market. AI-powered systems can amalgamate this and other relevant data to inform product development and quality control. Based on such insights, an IIoT network of machines and robotic devices can be automated to optimise product manufacturing in smart factories.
• Resilient supply chains: IIoT networks let supply chain managers know things such as where their products are, which suppliers have them, and how many are in stock. IIoT devices and machines can also be programmed on the fly to adapt to real-time events and disruptions, giving businesses built-in contingency planning and a competitive, resilient edge.
• Intelligent logistics: To meet the growing demand for speed and volume, logistics providers have had to augment their commercial vehicle fleets with networks of last-mile delivery partners using on-demand small vehicles (including even bicycles and scooters). By equipping such vehicle networks with IIoT and tracking devices or apps, supply chain managers can maintain a centralised view of every vehicle in their fleet—be it cargo ship or e-bike. Real-time data from IoT sensors can also help to consolidate loads, minimise waste, and speed up deliveries.
• Healthcare: From the patients’ perspective, IoT monitors and wearables can help them feel more in control of their care, all the while connected to their healthcare provider. For medical practitioners, the data provided by these devices can offer a more comprehensive picture of patient health. The result is a more informed and thorough approach to diagnostics, treatment, and general well-being. And in more practical applications, surgical IIoT devices are steadily improving to the point where remote surgery and advanced diagnostic devices will enable healthcare professionals in underdeveloped or isolated regions to share sensory input and collaborate in real time with some of the best doctors and nurses in the world.
• Agriculture: For businesses dependent on weather and natural forces, any tool that helps reduce risk and vulnerability is a welcome addition. The modern agriculture sector is using IoT solutions for everything from precision farming that distributes water and other resources as needed, to facilitating aeroponics in vertical farms through sensors that monitor temperature, humidity, and other factors to create an ideal indoor growing environment for plants.
• Smart building management: Buildings equipped with smart devices and sensors provide facilities managers with unparalleled visibility into operations, which they can use to save money, extend the lifespan of infrastructure, and increase energy efficiency. IIoT sensors collect granular, real-time data about the HVAC system, for example, which can be used to adjust heating in different zones, where and when needed. Sensors can also be used to detect leaks early to prevent flooding or to identify vibrations, crack formations, humidity exposure, and other structural integrity concerns in older buildings.
• Sustainable utilities and energy management: IIoT technology has myriad uses in the energy and utilities sector, from monitoring usage patterns to predicting demand, and optimising energy consumption. In distributed microgrids, it enables energy consumers with solar panels or other alternative energy sources to become “prosumers” – seeing how much power they are using and how much they can either sell back to the grid or redistribute as they see fit.

Next steps towards an IIoT transformation

A successful business transformation relies on good change management strategies and a commitment to regular and meaningful communication across the business. Building an IIoT network does not have to happen overnight. It can start with a modern cloud ERP to help you centralise and unify your business operations, and build gradually as you connect and integrate smart devices, smart teams, and smart systems.