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Top 10 Industrial IoT applications to spark innovation in 2023

By Nadejda Alkhaldi, Innovation Analyst
Published on

It’s difficult to produce and sell quality items when you don’t know where your assets are located at a given time. Or when your inventory is constantly running out of essential materials. Or when equipment unexpectedly breaks down despite scheduled inspection rounds. And on top of this, your supplier doesn’t bother to inform you about shipment delays or delivers spoiled items because the cooling system broke down and no one noticed.

Are you looking to take full control over your manufacturing process and monitor your supply chain? Then an Industrial Internet of Things solution might be exactly what you need.

Keep reading this article to discover top Industrial IoT applications that will ensure the unfortunate situations above don’t compromise your operations.

What is Industrial IoT, and how does it work?

The Industrial Internet of Things (IIoT) is the utilization of sensors to gather and process data from connected devices with the goal of understanding and improving the industrial processes. IIoT can also use actuators and programmable controllers to communicate with devices and make them act in a certain way.

The number of IoT devices is steadily growing worldwide. Statista reported 11.28 billion devices in 2021. And this number is expected to surpass 29 billion by 2030 as the demand for IoT grows. Ericsson states that for a factory to be considered “smart,” it needs to deploy 0.5 IoT devices per square meter.

So, how do IoT devices work together? And what do you need to know to use them at your organization?

The anatomy of IoT

IoT architecture consists of software and hardware components that interact together to aggregate, transmit, and analyze data coming from different devices. Below, you will find a brief description of the five main IoT layers. For a detailed explanation, check out our detailed guide on IoT architecture.

  1. Device layer. Covers various IoT devices equipped with sensors and actuators. Sensors gather data from the corresponding devices and transmit it as a signal to a processing unit. Actuators, on the contrary, receive commands — i.e., signals — from processing centers and make devices act upon them.

  2. Network layer. Spans communication technologies, such as Bluetooth, 4G/5G, and Wi-Fi, to mention a few examples.

  3. Edge computing layer. Comprises intermediary devices between IoT units and cloud servers. These devices process critical data locally and send the remaining information to the cloud at scheduled intervals, thus reducing infrastructure costs. While edge computing devices aren’t part of the traditional IoT architecture, they’re getting increasingly popular with the Internet of Things adopters.

  4. Device and application support layer. Receives, processes, and stores data gathered from IoT sensors.

  5. Application layer. Covers different applications that work on IoT data. This includes analytical algorithms, data visualization tools, software that issues commands to actuators, etc.

While the “traditional” IoT is customer-centric and captures how people interact with their smart devices, Industrial IoT focuses on enterprise-wide applications and implies large-scale deployments.

IIoT platforms for even greater benefits

IoT is not a new concept, and many industrial organizations use IoT sensors to gather data from connected devices. However, IoT is often deployed in isolated silos for each Industrial IoT application, which limits data sharing and restricts the benefits.

To mitigate this, organizations can benefit from the Internet of Things development services to build IIoT platforms that span the entire enterprise. This setup will break isolated IoT pipelines and establish a centralized point for managing IoT devices across different use cases. It will also allow you to integrate more data and have a unified view on all operations.

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Top 10 Industrial IoT applications

Here are 10 key Industrial Internet of Things examples that will help you save time and money without compromising quality:

  1. Predictive maintenance

  2. Quality control

  3. Supply chain management

  4. Asset tracking

  5. Inventory monitoring

  6. Remote equipment and production site control

  7. Energy management

  8. Automation

  9. Process optimization and advanced analytics

  10. Safety control

Predictive maintenance

Manufacturers go through 800 hours of equipment downtime annually, which is equivalent to 15 hours a week. Another research shows that unplanned device failure can cost a company as much as $260,000 per hour.

Fortunately, Industrial IoT can be applied to prevent equipment failure and cut down on associated expenses. IoT sensors placed on equipment and vehicles can gather data on its performance and condition, such as vibrations, voltage, and temperature. These sensors detect and report any suspicious changes and slight performance degradations, giving technicians enough time to interfere and fix the issue before it impacts the production process.

Volvo, one of the leading car manufacturers, outfits its trucks with IoT sensors that capture vehicle data and send it for analysis. Their comprehensive IoT platform can process millions of data records instantly. This tactic enables Volvo to reduce track repair time by 25% and diagnostic time by a whopping 70%.

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Quality control

IoT allows manufacturers to monitor their products at any stage, starting with raw materials, and all the way as the item moves along the production line. This even includes the amount of waste emitted during the manufacturing process. IoT sensors can continue gathering data even after the item is purchased. They can transmit information on customer satisfaction and keep track of any issues the client encounters with the product.

Recently, a research team deployed IoT sensors together with convolutional neural networks to identify defects in Printed Circuit Boards (PCBs) manufacturing before the products reached the final production stages. As a result, they could spot defected PCBs with 97% accuracy.

There are many benefits of combining IoT and AI, like in the IIoT example above. To learn more, check out this Artificial Intelligence of Things (AIoT) blog post from our innovation analysts.

Supply chain management

Industrial IoT systems allow managers to track different events across the supply chain. They can access real-time information on the location of materials in transit and get a notification if there is an unforeseen delay, accompanied with the supplier’s justification. Sensors also help monitor temperature, humidity, and other relevant conditions of transported goods.

In May 2021, DHL transported around 200 million COVID-19 vaccines to over 120 countries worldwide. The company used IoT sensors to monitor transportation conditions and ensure the temperature did not exceed the threshold, which would result in spoilage.

In another real-life IIoT application, California-based Golden State Foods uses IBM’s IoT trackers to monitor storage conditions while transporting meat.

Furthermore, deploying IoT in supply chains can help in logistics optimization as companies can identify shorter, less crowded routes. Enhanced with AI, such systems can predict traffic congestions, take into account weather conditions and accidents on the transportation route and make the necessary changes. Consider consulting artificial intelligence services vendors for comprehensive logistics optimization solutions.

An interesting example of combining AI and IIoT comes from a logistics innovation company. The client turned to ITRex to develop an AI-powered IoT system that allows companies to monitor cargo in real time, calculate shipping costs based on 60 parameters, fill in paperless documents, and more. Currently, this IIoT platform has over 25,000 users, including large players in the transportation sector, such as DHL and Maersk.

Asset tracking

Large facilities typically have too many assets that employees can’t keep track of. For instance, studies show that nurses waste around 10% of their time searching for equipment. This problem is not limited to healthcare. The same goes for large factories, stores, etc.

One of the Industrial IoT applications is that it can automate asset finding and monitoring. Companies can outfit their assets, such as finished goods, raw materials, tools, and packages, with radio-frequency identification (RFID) tags. These tags are scanned with RFID readers to display information on the corresponding item. Another option is to use equipment sensors that transmit signals over Bluetooth. If power consumption is an issue and you need long-range connectivity, opt for narrowband IoT (NB-IoT), which relies on low-power wide area network (LPWAN) technology.

In addition to locating items, IIoT-powered asset tracking can help you protect raw materials and avoid waste. For instance, if employees are working with large paint barrels, it’s tempting to grab the barrel that is the closest to the entrance point instead of walking through the barrel storage unit checking for expiration dates. With IoT tags, employees will be notified about the location of the barrels nearing their expiration date and receive a warning if they still grab the closest item.

There are many vendors who have their own IoT tracking systems. For instance, Bosch built a cloud-based Bluehound asset tracking solution, which relies on Bluetooth to transmit signals. This system was designed in collaboration with construction firms and can be integrated with popular enterprise-wide software used in manufacturing. Bosch claims the tags can withstand water and dust and their batteries can last up to two years. This system captures detailed asset-related information. For instance, it can understand when a tool was dropped. And if an item goes missing, the system can show where it was last seen.

In another example, Volvo uses IoT-powered trackers to track vehicles in its large truck plants, where they assemble around 72 vehicles per day.

Inventory monitoring

Another Internet of Things industrial application is fitting the inventory with IoT sensors that will transmit its status in real time. For example, if materials or manufactured products are overheated in storage, smart sensors will ask an IoT-enabled thermostat to lower the temperature in the storage unit.

Companies can combine Industrial IoT and analytics to rearrange inventory in an optimal way. For instance, the tools and raw materials that are used the most frequently will be moved closer to access points.

IIoT can monitor inventory levels and automatically place an order if stock decreases below a predetermined threshold. This eliminates the need for manual checks. If you are a retailer owning a store with electronic shelves, you can deploy e-labels. Powered by Bluetooth beacons, these tags allow customers to place orders simply by pressing on them. Suppliers will receive order alerts and can either confirm or decline. The e-label can also display “on-order” tag to prevent customers from placing repetitive orders.

Levi Strauss, a clothing company, deploys RFID tags to monitor stock levels. This enables the company to know how many items they still have left of each model and when the new arrivals are expected.

Remote equipment and production site control

Giving managers control over remote equipment is another important Industrial IoT application. Sensors can monitor machinery and allow human operators to activate equipment, shut it down, or change the settings. For instance, if water pump leakage is detected, the technician can deactivate the pump without having to access it physically. This use case is particularly convenient for machinery installed in hard-to-reach locations.

Speaking of remote locations, IIoT can be deployed to control tower beacon lights. These lights have very specific requirements, and any organization that owns towers, like the telecom sector, has to conform to these standards. IoT sensors can make sure the lights are located at the right height, and have the required color and brightness, and notify the operator immediately in the case of violations.

IIoT is also helpful in monitoring remote sites. For example, the British oil and gas company Shell, partnered with an IIoT startup Hiber to install IoT sensors in their wells. The sensors are supposed to gather information on the wells’ pressure and temperature to minimize human intervention. This is not the only IoT industrial application that Shell deployed. The oil and gas giant also used the technology to protect its pipelines. The company claims to have saved $1 million deploying IoT sensors in its oilfields.

Energy management

Companies can attach IoT sensors to its infrastructure to monitor the environment and cut on energy consumption when possible. For instance, sensors can turn off the lights when everyone leaves the building. They can also gather and analyze data on the heating and ventilation system to find the optimal performance.

Another application of Industrial IoT is detecting when one piece of equipment starts to excessively consume electricity. This is often an indication that the machine is damaged and needs closer inspection.

The Chinese company Chengdu Xihui Water Environmental Co., Ltd relied on MindSphere, the Industrial IoT as a service solution from Siemens, to save on energy consumption. The company operates wastewater treatment stations, and energy bills account for almost half of their operational costs. Chengdu Xihui deployed IoT sensors on its equipment to gather real-time data. After thorough analysis, the company understood when the equipment is at its highest energy consumption rate and managed to match this with off-peak electricity prices, reducing the expenses by 10%.


With the help of IIoT and robotics, it’s possible to automate tedious tasks that are typically performed by human employees.

One example of this Industrial IoT application comes from Amazon. The retail giant uses several types of robots at its warehouses to automate tedious and even dangerous tasks. For instance, Cardinal robot can lift packages, read their label with the help of AI and computer vision, and place the right package into a GoCart to move packages within the facility. Cardinal can easily lift heavy packages that can cause injuries in human employees.

Proteus is another robot that can move GoCarts through order fulfillment centers while navigating around people and robots.

IoT-based automation is not limited to warehouse-related activities. Robots can also take over production tasks. For example, Lear Corporation, a car seat manufacturer, relies on UR5 robots to assemble car seats. UR5 works alongside human employees and can perform tasks, such as screwdriving, lifting, and placing seats.

Robots can also replace humans in toxic environments, like painting facilities with poisonous emissions.

Process optimization and advanced analytics

Another Industrial IoT application example is spotting opportunities for process and product optimization with the help of analytics. IoT enables manufacturers to identify and predict bottlenecks in production processes and address the issue preemptively. The technology can also help update performance benchmarks. These production standards, such as the amount of time it takes to produce a product part, are set and rarely updated. Tools like Machine Metrics allow managers to gather performance data and optimize job standards to set realistic deadlines and prices of new products.

Applying advanced analytics to data incoming from purchased products helps companies understand how customers actually utilize the items, and update the warranty policy accordingly.

IoT sensors attached to packages enable companies to monitor the products during transportation and optimize the packaging to minimize item damage.

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Safety control

IoT can contribute to workers’ safety by monitoring the environment, employee behavior, and compliance with safety protocols. Employees working at high altitudes or operating heavy machinery can wear sensors that will evaluate their body temperature, perspiration, and working technique, and alert managers if they detect a likelihood of a hazardous scenario. Given that musculoskeletal disorders are responsible for 33% of workplace injuries, these sensors can significantly enhance safety.

For instance, a workplace wearables firm called Kinetic built a smart device the size of a smartphone. It can detect posture and movements that are highly dangerous on the job and notify the employee immediately through light vibrations.

Another example of IIoT comes from Uruguay, where a biofuel plant supplies all workers with a smart helmet. It contains sensors that track people’s movements and detect if someone falls or spends too much time in an area with noxious gasses.

Factories can also enhance safety by deploying environmental sensors. These devices can monitor the surroundings for dangers. For instance, they can detect extreme temperatures that can result in a fire and spot any hazardous gas leakage, and alert workers.

On a final note

Industrial IoT has many exciting applications. It can decrease time and costs associated with equipment failure, take over tedious tasks that pose health risks for human employees, make sure the stock is always replenished so that you don’t get stuck waiting for raw materials. And these are just a few of its benefits.

However, there are challenges associated with deploying this technology. The main problem with IoT applications in industry is maintaining data security. As more information is aggregated, processed, and stored, the higher the risk of cyberattacks. Another challenge is the costs associated with IoT solutions. Keep these aspects in mind when choosing your IIoT vendor. We can help you equip your devices with sensors, build a platform that enables you to manage the IoT devices, develop custom big data analytics solutions tailored to your business needs.

What is Industrial IoT, and how does it work?The anatomy of IoTIIoT platforms for even greater benefitsTop 10 Industrial IoT applicationsPredictive maintenanceQuality controlSupply chain managementAsset trackingInventory monitoringRemote equipment and production site controlEnergy managementAutomationProcess optimization and advanced analyticsSafety controlOn a final note
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