What is industrial IoT, and how is it different from consumer IoT?Here’s our guide to the world of IIoT.
By PAT WILBUR via https://www.hologram.io
The industrial Internet of Things (IIoT) applies IoT technology to manufacturing, energy production, and construction industries. When machines are connected, enterprises can track their activity, progress, and maintenance needs, ultimately improving their operational efficiency. Also called Industry 4.0, IIoT promises to revolutionize manufacturing processes and help organizations take advantage of all data types.
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”“smar”” 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 on improving consumers’ everyday lives with conveniences like thermostats, security cameras, and automated lawnmowers that can be controlled from a smartphone.
IIoT
By contrast, IIoT improves performance and 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 cross-country buses, or multi-function sensors can be 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 need repair.
What are the challenges of IIoT adoption?
IIoT promises dramatic results for companies across many industries, but adoption can be challenging. Organizing a mass device deployment is complicated and often requires overhauling 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 many 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, bringing more protection and peace of mind to 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 emerging products 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 the company’s equipment simultaneously, 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 is just beginning. Now, they need to keep track of all those devices. Many IoT platforms promise to do this and may deliver the required environmental or machine monitoring data for their harvesting devices. However, companies must also access detailed data about the IIoT devices—their connectivity status, location, and health. Suppose an IIoT vehicle tracking device suddenly goes offline or shows up in an unexpected location. In that case, IT leaders at the company need to be alerted to 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 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 comes from various types of devices in multiple formats, for example, it must be converted to a common format and sent 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 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. However, predictive maintenance also applies to the IIoT devices themselves. If the device detects a problem in its software or system, it can alert the company through the IoT platform. In many cases, maintenance on both machinery and IoT devices can be performed remotely.
Bridging the IT/OT gap
In many industries, especially manufacturing companies, there has 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 allows it to stream real-time information from a factory floor and 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 IoT sensors. Better visibility of supply chains means companies can anticipate their needs and plan accordingly.
Cost savings
The efficiencies IIoT brings to the industry are reflected in cost savings, particularly in 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 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 manufacturing sites’ tasks like barcode reading and quality control. 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 can learn and adapt based on training and experience. The OneTracksolution for warehouses is an example of AI vision for IIoT. AI-powered cameras attached to forklifts measure everything that’s happening around them, yielding insights about the best routes for the movement of goods, workflow recommendations, and safety alerts.
Connected construction sites
For construction contractors, tracking assets like excavators, vehicles, and tools can be a constant juggling act. Connecting powered and non-powered assets with GPS modules or RFID tags are one-way IIoT can benefit this industry. For example, Hilti’s On! The track system keeps 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 install 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 isEveractive’ss 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 and analyzed against algorithms to yield predictive analytics and other helpful recommendations.
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, 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 for industrial buildings. For example, it 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 concerned 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 can even 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 can connect with them easily. However, 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 this problem, making collecting data from older machinery possible. Amper’ss solution doesn’t require PLC upgrades or IT integration. Its non-invasive sensors are installed in the equipment’s power supply and connected to a cellular gateway for 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 adding 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 embrace this emerging technology. With IoT and enhanced wireless connectivity, some robots can safely navigate a manufacturing facility. For example, Mobile Industrial robots make rolling robots designed to carry loads up to 1,000 kg (around 2,200 lbs), allowing factories to automate 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 is 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 the 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 directly impact 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 greatly increase data speeds.
Private 5G networks will also play a role in IIoT as they provide dedicated connectivity to on-site devices. This allows manufacturers to tailor their network to meet the needs of their facility and 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 is 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 by keeping at least some data processing at the network edge rather than sending everything to the cloud. Keeping sensitive data on the premises adds safety and privacy to industrial sites. 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 evolving as compact, low-cost processors such as the Raspberry Pi have emerged. 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 how many companies do business, resulting in enormous cost and time savings with increased efficiencies.
The possibilities, as they say, are endless.
