What is IIoT?

The industrial internet of things (IIoT) applies IoT technology to industries like manufacturing, energy production, and construction. When machines are connected, enterprises can track their activity, progress, and maintenance needs—and ultimately improve their operational efficiency. Also called Industry 4.0, IIoT promises to revolutionize manufacturing processes and help organizations take advantage of all types of data.

IIoT vs. IoT: What’s the difference?

IoT can be difficult to define, but ultimately it means technology in the environment around us interacting with other technology and with us, creating a “smart” environment. As a subcategory of the broader IoT, IIoT also relies on three layers of technology: hardware (the sensors and devices installed in factories or industrial sites), firmware (software on each device that allows it to send, receive, and process data), and connectivity (the method or protocol that enables devices to “talk” to one another, such as Wi-Fi or cellular).

Consumer IoT

IIoT is often defined in its relationship to consumer IoT, which is focused improving the everyday lives of consumers with conveniences like thermostats, security cameras, and automated lawnmowers that can be controlled from a smartphone.

IIoT

By contrast, IIoT improves performance and increases efficiency at factories and manufacturing sites. For example, an IIoT sensor connected to an assembly machine on the factory floor can sense when it’s about to overheat and send an alert to trigger preventive maintenance before it completely breaks down.

Mass deployments

While consumer IoT products are typically used individually or a few at a time, IIoT deployments often involve hundreds, thousands, or even tens of thousands of devices. Vehicle trackers can be installed in an entire fleet of buses traveling cross-country, or multi-function sensors attached to factory equipment to generate reports about productivity and maintenance. Mass IIoT deployments let organizations see the big picture of all their assets—where they are, what they’re doing, how much they’re producing, and whether they’re in need of repair.

What are the challenges of IIoT adoption?

IIoT promises dramatic results for companies across many industries, but adoption can be fraught with challenges. Organizing a mass device deployment is naturally complicated and often requires an overhaul of the company’s previous methods and processes. A few of the most common barriers to IIoT adoption include:

Security

In general, IoT security is a major concern. That’s because as a new and uncharted terrain, the world of IoT involves a lot of moving parts and pieces—each of which can become a doorway for hackers. IIoT security in particular is a point of stress because dependence on a single IT system means a potential for tremendous damage if that system is compromised. If there’s a vulnerability in the software, hackers could take control of IIoT devices and start manipulating their behavior. Security standards for IIoT are beginning to emerge, and they will bring more protection and peace of mind for companies interested in adopting new technologies.

Connecting legacy equipment

Many companies still use older, legacy equipment that wasn’t designed to be part of the IoT. While products are emerging that can connect these older machines, finding the right drivers can be tricky—and translating all the data into a compatible format is another problem. One option is to upgrade all a company’s equipment at once, but that’s an expensive and often impossible feat. Realistically, most industrial organizations will transition to IIoT systems gradually, replacing older equipment as it becomes unusable with newer IIoT-ready devices.

Device management

When a manufacturing company deploys hundreds or thousands of devices and gets them up and running, they might feel like the work of their IIoT adoption is over—but really, it’s just beginning. Now, they need to keep track of all those devices. Many IoT platforms promise to do this, and may deliver the needed environmental or machine monitoring data the devices are harvesting. But companies also need to access detailed data about the IIoT devices themselves—their connectivity status, location, and health. If an IIoT vehicle tracking device suddenly goes offline or shows up in an unexpected location, IT leaders at the company need to be alerted so they can deal with the potential problem.

Data storage and management

Massive deployments of IIoT devices generate a lot of data. Unless organizations are prepared to deal with the oncoming tidal wave, their systems will be overwhelmed—both by the amount of data and the cellular usage of so many IoT devices. Typically, cloud platforms provide the best solution for storing IIoT data, but companies also need ways to manage it successfully. If data is coming from different types of devices in various formats, for example, there must be a way to convert it to a common format and send it to third-party analytics software. Without a clear path from the edge to the cloud and beyond, data can get lost in the shuffle—and if it’s missing or delayed, it’s pretty much useless.

What are the benefits of IIoT?

While companies adopting IIoT systems will meet some challenges, they stand to reap many benefits once a device deployment is running successfully. Here are a few areas where IIoT can provide tremendous value:

Predictive maintenance

Knowing ahead of time when a factory robot is on the verge of breakdown is a huge advantage for manufacturing companies. IIoT devices can provide that advance notification, allowing operators to deal with emerging problems before they cause unexpected (and costly) downtimes. But predictive maintenance also applies to the IIoT devices themselves—if the device detects a problem in its own software or system, it can send an alert to the company through the IoT platform. In many cases, maintenance on both machinery and IIoT devices can be performed remotely.

Bridging the IT/OT gap

In many industries, especially manufacturing companies, there’s always been a gap between information technology (IT) and operational technology (OT). This gap led to data silos and an incomplete picture of the company’s performance. By providing an overarching system that both teams can access and participate in, IIoT makes it possible to stream real-time information from a factory floor along with data from many other areas of operations into the same cloud platform. For example, an automobile company collects data from robots on multiple factory floors, combines it with data from operational teams and supply chains, and runs analytics. They get comprehensive reports on productivity that they can use to increase efficiencies and make better decisions.

Improved supply chain visibility

IIoT devices that track vehicles, crates, and packages can also provide better visibility into the supply chain for industrial companies. For example, a consumer goods company can track the status of shipments across an ocean or even across a warehouse with RFID or cellular IIoT sensors. Better visibility of supply chains means companies can anticipate their needs and plan accordingly.

Cost savings

The efficiencies that IIoT brings to industry are reflected in cost savings, particularly around energy use. Connected buildings, which use IoT sensors to monitor and control lighting and HVAC usage, can reduce energy bills by significant margins. One California-based company claims to reduce its customers’ lighting costs by up to 70 percent.

AI applications

Using the data IIoT sensors collect, artificial intelligence can enhance efficiencies and deal with problems, sometimes without human intervention. An appliance manufacturer, for example, can use AI-powered computer vision technology to scan products for major errors. By comparing it to stored information, the AI-powered device can “look” at a toaster and immediately tell if there’s a missing part or a defect.

IIoT across major industries

Many major industries can benefit from IIoT adoption, and many are in the process of doing so—in fact, 92% of industrial organizations have adopted IoT in some way in 2019. Sixty-eight percent of industrial leaders use IoT for monitoring and maintenance, while 54% said they use IoT to power remote operations. Some of the industries embracing IoT include:

• Mining
• Manufacturing
• Warehouses
• Oil and gas
• Container shipping
• Construction
• Wind farms
  

9 interesting IIoT use cases

Many industrial sectors are adopting IIoT—some more quickly than others. Manufacturing plants, mining operations, logistics and transportation fleets, construction firms, and energy companies are just a few of the industries that stand to benefit from IIoT, and many of them are already pursuing connected solutions. Let’s take a closer look at some interesting IIoT use cases.

AI vision

Machine vision has long been used for tasks like barcode reading and quality control at manufacturing sites. Now, advancements in artificial intelligence (AI) coupled with existing vision technology are yielding new applications and capabilities. AI vision is based on deep learning—machines take a statistical approach, and they’re able to learn and adapt based on training and experience. The OneTrack solution for warehouses is an example of AI vision for IIoT in action. AI-powered cameras attached to forklifts measure everything that’s happening around them, yielding insights about the best routes for movement of goods, workflow recommendations, and safety alerts.

Connected construction sites

For construction contractors, keeping track of assets like excavators, vehicles, and tools can be a constant juggling act. Connecting powered and non-powered assets with GPS modules or RFID tags is one way IIoT can benefit this industry. For example, Hilti’s On!Track system keep track of tools and equipment on job sites. The cloud-based software management system helps contractors manage tools, find missing equipment, and keep track of preventative maintenance needs.

Sensor-filled factories

As factories embrace Industry 4.0, they’re installing sensors to gather data about everything from asset location to quality control. Sensors work together to provide real-time data, and machine learning capabilities mean management software can create algorithms to predict outcomes and take immediate action if something goes wrong or a machine is about to break down. One example of the many types of factory sensors is Everactive’s steam trap monitoring devices. Mounted on steam traps within factories and processing plants, the devices monitor levels of escaping steam and send out automated alerts if they detect a leak or other issue. They also run on harvested energy, and don’t require battery changes or other maintenance.

Intelligent agriculture

IIoT is powering precision agriculture—using sensors and analytics to monitor fields and make targeted decisions about caring for crops. Farmers might install sensors to monitor factors such as moisture in the soil, location of equipment, and status of water tanks and irrigation systems. Phytech attaches IIoT sensors directly to plants to monitor micro-variations of stem diameter, which are stress indicators. The data is transmitted to the cloud, where it’s analyzed against algorithms to yield predictive analytics and other recommendations that are helpful in decision-making.

Smart buildings

While smart home devices are novelties in consumer IoT, smart buildings—also known as building automation systems (BAS)—are the IIoT side of the same coin. Today’s automated BAS can manage HVAC settings, window blinds, lighting, and other systems throughout the building. They can also detect how many people are in a particular section of the building and adjust ventilation systems accordingly—a process called demand control ventilation (DCV), which can result in significant cost savings. Adopting BAS can save 15% or more on utility and operating costs, making the initial investment well worth it for industrial buildings. For example, Iota offers IoT sensors for remote monitoring and an interactive platform to give building managers the tools and alerts they need to optimize energy consumption.

Wearables for workers

Worker safety is always a concern in industrial settings like factories, mining facilities, and oil rigs. With the introduction of IIoT, developers are imagining new ways to keep people safe. Wearable sensors can monitor environmental conditions and workers’ vital signs like heart rate and temperature. One example is WakeCap, a smart hardhat that reports project management action along with worker safety information. It’s even able to provide contact tracing data to help stop the spread of COVID-19 among workers.

Digitizing legacy equipment

Newer machinery often includes IIoT components, or at least has the capacity to connect with them easily. But industries face complications when they want to incorporate IIoT sensors yet still rely on older legacy equipment that wasn’t designed to connect. Several companies have developed solutions to solve this problem, making it possible to collect data from older machinery. Amper’s solution doesn’t require PLC upgrades or IT integration. Its non-invasive sensors are installed to the equipment’s power supply and connected to a cellular gateway to allow system calibration. Then, managers can access data via mobile dashboards from their web-based app.

Automated mining

Historically risky for workers, mining has benefited from the addition of connected equipment such as autonomous vehicles, drills, loaders, and other tools. Automation is becoming the global standard for mining operations, and it promises to reduce costs and increase production capacity. One example of IIoT in mining is Sandvik’s intelligent mining trucks. A software platform turns the trucks into unmanned robots, allowing mining operators to oversee them from above ground. The trucks use a positioning system to detect obstacles and other vehicles, and navigate through marked safety zones.

Free-roaming robots

While free-roaming robots may still be science fiction to some factory workers, other manufacturing plants are embracing this emerging technology. With the advent of IoT and enhanced wireless connectivity, some robots are able to navigate through a manufacturing facility safely. For example, Mobile Industrial Robots makes rolling robots designed to carry loads up to 1,000 kg (around 2,200 lbs), allowing factories to automated and optimize internal transportation of heavy items and pallets. The robots evaluate possible routes to their destination and choose the most efficient one available, maneuver safely around obstacles, and stop if a person blocks their path.

What's the future of IIoT?

As IIoT continues to develop and adapt to the needs of different industries, more organizations will launch or expand device deployments. Concurrent innovations such as the evolution of cellular networks and development of edge computing will enable a fuller realization of IIoT’s potential.

How 5G will transform IIoT

The growth of 5G cellular connectivity will have a direct impact on IIoT, providing the infrastructure needed to power massive deployments within factories and other industrial sites. Industrial 5G promises to improve connectivity, reduce latency, add flexibility—and of course, greatly increase data speeds.

Private 5G networks will also play a role in IIoT as they provide dedicated connectivity to on-site devices, allowing manufacturers to tailor their network to meet the needs of their facility—and to keep data local and secure. Many regions of the world are setting aside dedicated spectrum ranges purely for IIoT use, ensuring that connectivity is always reliable. For example, Japan chose the 28GHz band for industrial use.

While 5G appears poised to enable IIoT on a grand scale, it’s still a new technology and will likely take several years to unfold.

The evolution of edge computing

Edge computing is also part of the future of IIoT. Industries save time, money, and resources when they keep at least some data processing at the network edge rather than sending everything to the cloud. Keeping sensitive data on premise adds additional safety and privacy at industrial sites. And processing at the edge is essential in some IIoT use cases (like agriculture) where IIoT devices are far afield and stable connectivity is difficult to achieve. Edge computing continues to evolve as compact, low-cost processors such as the Raspberri Pi have come on the scene. While the prevalence of edge computing is likely to keep growing, IIoT will still rely on the cloud for tasks like in-depth data analytics and information storage.

Major growth of IIoT is only just beginning—but it’s likely to be rapid. When fully realized, the combination of sensors, AI capabilities, and analytics will revolutionize the way many companies do business, resulting in enormous cost and time savings with increased efficiencies.

The possibilities, as they say, are endless.