What is the Industrial Internet of Things (IIoT)?
Fifty years ago, when we thought about futuristic industrial technology, we often imagined increasingly agile robots, with hands and legs to better mimic human dexterity. What the rise of the Industrial Internet of Things has showed us, is that we were only partially right. Of course, industrial machinery and robots have without question become more sophisticated, but where the true advancement has come, is in the ability for those industrial devices to exist in a connected network in which they can gather data and talk to each other – and to central business systems – in real time.
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 stands for the Industrial Internet of Things, and as the name suggests it refers to the use of Internet of Things technology (connected machines, devices, and sensors) in industrial applications. When run by a modern ERP with AI and machine learning capabilities, the data generated by IIoT devices can be analysed and leveraged 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 lies less in how they work and more in how they are used. The bulk of the world’s IoT solutions tend to have individuals as their end users and are most commonly incorporated into things like smart watches, voice-controlled digital assistants, or smart appliances and TVs.
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 need the capacity to send and receive the massive volumes of data generated by machines and devices. This has traditionally been both enabled and limited by the power of Wi-Fi connectivity. But 5G and other advances in cellular networks are changing this calculus, increasing bandwidth to manage 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 faster for more efficient data processing and longer battery life.
- IIoT sensors: Today, sensors are typically built into new industrial equipment and machinery. But analog machinery and manufacturing equipment can also be fitted with IoT gateway devices such as cameras and gauges. This lets IIoT assets 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 leverage 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-premise – 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 deeper, 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 make it possible for 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 get bigger 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 connectedness that gives life to IIoT networks also puts them at risk. While most companies have tight 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 up 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 aren’t already, security strategies must become a top priority for any modern business.
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.
- 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 like 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 bikes and scooters). By fitting such vehicle networks with IIoT and tracking devices or apps, supply chain managers can keep 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 amalgamate 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 delivered by these devices can give a more complete picture of patient health. The result is a more informed and thorough approach to diagnostics, treatment, and general well-being. And in more hands-on applications, surgical IIoT devices are steadily improving to where remote surgery and advanced diagnostic devices will allow healthcare professionals in underdeveloped or isolated regions, to share sensory input and partner in real time, with some of the best doctors and nurses in the world.
- Agriculture: For businesses dependent upon weather and natural forces, any tool that helps reduce risk and vulnerability is a welcome addition. According to Forbes magazine, 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 outfitted with smart devices and sensors give facility managers unprecedented visibility into operations that they can use to save money, prolong infrastructure health, 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 discover leaks early to prevent flooding or to detect 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 allows 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 best see fit.
Next steps to an IIoT transformation
A successful business transformation relies upon 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.
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