In short

• IoT initiatives appear more successful than ever, as 92% of enterprises report positive ROI from IoT use case implementations, according to IoT Analytics’ 418-page IoT Use Case Adoption Report 2024.
• The number of IoT use cases being adopted by enterprises grew 53% between 2021 and 2024.
• Complexities related to IoT use case adoption appear to be easing somewhat, which appears to be fueling the adoption growth and ROI.
• Enterprise IoT use case investments continue to grow in 2024, but at a slower pace than in previous years.
• IoT Analytics presents the top 10 IoT use cases, with process automation as the #1 adopted IoT use case.

Why it matters?

• For IoT vendors: With the success of IoT initiatives and the growing adoption rate, IoT vendors can learn about what use cases end users are adopting and tailor their offerings.
• For IoT adopters: Adopting IoT use cases has shown ROI, in many cases, within two years. IoT can help adopters streamline their operations and support digitalization efforts.

Status of IoT initiatives in 2024: More successful than ever before

Over 90% of IoT use case projects have positive ROI. For years, IoT Analytics has been unable to validate common claims that most IoT projects are unsuccessful, such as the following:

• Cisco Survey Reveals Close to Three-Fourths of IoT Projects Are Failing
• It’s the last IT/OT mile that matters in avoiding Industry 4.0’s pilot purgatory
• Why has the Internet of Things failed?

According to IoT Analytics’ research found in the 418-page IoT Use Case Adoption Report 2024 (published July 2024)—which is based on a survey of 200 end users of IoT applications and analyzes 27 IoT use cases—91.7% of organizations have seen ROI from the different IoT use cases they adopted, a 13-percentage-point climb from similar IoT Analytics research in 2021. Further, compared to 2021, 53% more IoT use cases are being adopted by organizations (either in the process of rolling out a use case or have already completed a project), signaling a healthy state of IoT.

IoT project complexity has reduced. In 2021, many respondents to a similar IoT use case survey noted the need for proofs of concept and testing since IoT projects and their technical setups can be complex. However, in 2024, the complexities of usage and onboarding/setup of IoT use case projects ranked 5th and 6th, respectively, in terms of challenges. In IoT Analytics’ opinion, this drop in perceived complexity appears to largely fuel the strong growth in IoT use case adoption.

Note: The report looks at IoT use cases that apply to most organizations and does not consider industry-specific use cases such as smart heating, ventilation, and air conditioning (HVAC) (applicable only to buildings) or smart transportation systems (applicable to cities).

The 10 most adopted IoT use cases

Most IoT use cases serve smart operations. The top 10 IoT use cases in 2024 have changed quite a bit since 2021; however, the distribution of use cases by category within the top 10 remains the same: 6 smart operations use cases, 3 smart supply chain use cases, and 1 connected product use case.

Below are the top 10 use cases in 2024, including how IoT Analytics defines them and which organizational KPIs are most affected by each. Also provided are select quotes and implementation examples for some of the use cases from the report.

Note: Each use case and definition below is based on IoT applications—some terms may have broader definitions outside of IoT.

1. Process automation

Process automation definition (by IoT Analytics)
The integration of IoT to automate routine processes, enhancing productivity and accuracy

Nearly 3/5 of organizations have adopted process automation. Leading as the most adopted IoT use case at 57.5% of organizations is process automation. This is a stark rise from the 33% adoption rate seen in the 2021 IoT use case report, where it was the second-ranked use case.

Process automation enables companies to streamline and automate processes by integrating interconnected devices and sensors with both new and legacy equipment, such as PLCs and IPCs. This use case helps to reduce the need for manual intervention, increasing efficiency, minimizing errors, and enhancing safety. Technologies such as IoT sensors and edge computing play a crucial role in enabling real-time data collection, analysis, and decision-making. By incorporating IoT into existing systems, companies can optimize workflows, improve production quality, and implement predictive maintenance.

Most important KPI affected

The top KPI affected by process automation is labor efficiency. On average, a major rollout of this use case improves labor efficiency by 8.2%.

Implementation example

When Burnley Brewing, an Australia-based craft brewery, approached its maximum capacity as demand for its beverages grew, it decided to expand. In doing so, it decided also to include automation in its processes. Burnley partnered with Australia-based contract electrical and engineering firm Bon Industry, which leveraged US-based industrial automation technology provider Rockwell Automation’s FactoryTalk Craft Brew—a process management and automation system developed specifically for the brewing industry. IoT sensors, PLCs, and other action-enabling hardware were placed throughout the brewing process, all connected to FactoryTalk Craft Brew for data collection and process actioning. As a result of this solution, Burnley Brewing lessened the labor of its brewers across the brewing process, from milling and mashing grain at the beginning to controlling fermenters and conditioning tanks near the end.

2. Quality control and management

Quality control and management definition (by IoT Analytics)
Integrating IoT (e.g., machine vision) to enhance quality processes

Quality control and management climbed 5 places since 2021. 55% oforganizations have adopted  IoT-based quality control and management. In 2021, this use case was 7^th in adoption at 30%, which marks a significant climb. A reason for this climb could be its quick payoff: 53% of companies that have implemented this use case reported amortization in less than 24 months.

Quality control and management allows companies to monitor critical factors like temperature, humidity, and pressure during production. This real-time data allows for immediate detection of quality deviations, enabling swift corrections to prevent defects. IoT solutions can be integrated into both new and legacy equipment, with machine learning analyzing the data to predict potential issues before they arise.

Most important KPI affected

The top KPI affected by quality control and management is, no surprise, product quality. On average, a major rollout of this use case improves product quality by 4.6%.

3. Energy monitoring

Energy monitoring definition (by IoT Analytics)
Integrating IoT to monitor energy consumption for individual assets

Companies plan to invest more in energy monitoring than any other smart operations use case. Adoption-wise, energy monitoring has risen to 55%—up from 20% in 2021.It is the rising star among IoT use cases, as new sustainability strategies and high electricity prices (especially in Europe) have led companies to use IoT devices and sensors to closely monitor individual assets’ energy consumption. Within the smart operations category, it has the highest expected investment increase between 2023 and 2024 at 3.5%.

Most important KPI affected

The top KPI affected by energy monitoring is costs. On average, a major rollout of this use case reduced related costs by 8.1%.

4. Real-time inventory management

Real-time inventory management definition (by IoT Analytics)
Utilizing IoT for tracking inventory levels in real-time to optimize stock and reduce shortages or excesses

Real-time inventory management leads smart supply chain use cases. 54% of respondents shared that their companies have either fully rolled out or are rolling out real-time inventory management. With the supply chain issues and economic uncertainty following the COVID-19 pandemic, companies have sought smarter inventory management solutions to prevent stockouts and overstocking. In fact, adoption of this use case climbed 35 percentage points between 2021 and 2024, and within the smart supply chain category, it is expected to receive the largest investment increase between 2023 and 2024 at 5.7%.

Most important KPI affected

The top KPI affected by real-time inventory management is the return on equity (ROE)/return on capital employed (ROCE). On average, a major rollout of this use case improves ROE/ROCE by 8.1%.

Implementation example

In 2022, Tyson Foods, a US-based multinational food company, wanted to automate time-consuming manual processes like inventory counts. The company already used computer vision for many of its processes but sought to incorporate machine learning to improve operational efficiency, among other goals. Leveraging AWS’s Panorama and SageMaker services, Tyson Foods implemented a computer vision-based, real-time inventory management system to deploy a detection model that automated chicken tray counting and identified faulty carriers. This real-time inventory management solution saved Tyson Foods an estimated 15,000 labor hours annually in each facility and helped it avoid over- or underproduction.

Additional insights from the IoT Use Case Adoption Report 2024
The report dives into the challenges companies face when implementing IoT use cases, conveyed by industry, region, and company size. Looking at the process manufacturing industry as an example, 46% of respondents, on average, marked “Integration into legacy systems” as a severe or major challenge, making it the top challenge faced by that industry. “Privacy concerns” and “IT and data security concerns” ranked as the 2nd and 3rd top concerns.

5. Supply chain track and trace

Supply chain track and trace definition (by IoT Analytics)
Employing IoT for monitoring the location, condition and/or status of products and materials along the supply chain

Most adopters see fast amortization with supply chain track and trace. Riding just behind real-time inventory management is supplychain track and trace, also at a 54% adoption rate. Approximately 60% of respondents experienced amortization in less than 24 months—second of all IoT use cases in this regard.

Connected sensors, GPS devices, LPWAN, and satellite technologies—all part of IoT’s contribution to supply chain track and trace—help companies monitor and manage the movement of goods throughout their entire supply chain by providing real-time visibility into the location, condition, and status of shipments. Advanced analytics further enhance supply chain operations by predicting disruptions and optimizing routing. With this use case, companies can reduce losses, improve delivery accuracy, and enhance compliance with regulatory requirements.

Most important KPI affected

The top KPI affected by supply chain track and trace is on-time delivery. On average, a major rollout of this use case improves on-time delivery by 8.5%.

Adopter quote

“The drivers drive with more foresight, the wearing parts last longer, the number of accidents goes down, the diesel consumption goes down—the stress is less.”

Oliver Nocke – Fleet Manager, Roman Mayer Transport & Logistik (via Samsara)

6. Operations planning and scheduling

Operations planning and scheduling definition (by IoT Analytics)
Leveraging IoT for real-time scheduling and planning to improve operational efficiency

Energy companies expect more investment in operations planning and scheduling. 53% of respondents shared that their respective companies have either rolled out or are currently rolling out operations planning and scheduling tools. Approximately 75% of companies in the energy sector are planning to increase investment in this use case in 2024, with an average increase of 5.5%.

By integrating IoT technology with planning systems, companies gain up-to-the-minute insights into production status, machine availability, and workforce capacity, allowing for dynamic adjustments to schedules, which helps reduce downtime and ensure optimal use of assets. Algorithms can further analyze the data to predict demand, identify bottlenecks, and suggest the most efficient scheduling options, resulting in improved operational efficiency and reduced lead times. Many (but not all) of the rollouts are tied to existing planning and scheduling software, such as manufacturing execution systems in the manufacturing sector, energy management systems in the energy sector, or building management systems in the buildings sector.

Most important KPI affected

The top KPI affected by operations planning and scheduling is labor efficiency. On average, a major rollout of this use case improves labor efficiency by 7%.

7. On-site facility track and trace

On-site facility track and trace definition (by IoT Analytics)
Employing IoT for real-time tracking and tracing of assets on a site (e.g., in a factory or warehouse)

Wholesale and retail expected to lead in on-site facility track and trace investment. Half of the organizations in the survey have adopted some form of on-site facility track and trace. Of those companies in the wholesale and retail segment that are testing or adopting this use case, 56% expect to increase investment, with an expected increase of 13% on average. Second to them are companies in the healthcare industry at 55%. On-site facility track and trace makes sense for these two segments, as tracking and locating products within a warehouse or equipment in a healthcare facility can aid in timely shipments or urgent medical needs.

Most important KPI affected

The top KPI affected by on-site facility track and trace is on-time delivery. On average, a major rollout of this use case improves on-time delivery by 7.8%.

Adopter quote

“Track and trace is a risk mitigation initiative for retailers, making it easier to identify products in the event of a recall, reducing exposure to costly lawsuits and improving overall compliance.”

John Merrill – CFO, ReposiTrak, February 14, 2024

8. Asset performance optimization

Asset performance optimization definition (by IoT Analytics)
Utilizing IoT to enhance operational efficiency and effectiveness of assets

Asia-Pacific companies to lead in asset performance optimization investment growth. Coming in with an adoption rate of 48% is asset performance optimization. This use case is expected to see a slight decrease in investment in 2024, with Asia-Pacific companies being the only ones foreseeing increased investment by 5% on average.

IoT for asset performance optimization is the modern version of asset performance management, which describes methods of capturing and integrating data, visualizing it, and analyzing it to improve the reliability and availability of physical assets. It combines state-of-the-art data-capture and integration tools (like IoT gateways) and software tools (like IoT platforms) to analyze how assets can operate and be maintained at optimum levels (e.g., optimized asset speed settings, optimized material input settings, or optimized maintenance intervals).

Most important KPI affected

The top KPI affected by asset performance optimization is overall equipment effectiveness (OEE). On average, a major rollout of this use case improves OEE by 9.5%.

Implementation example

When US-based Longroad Energy acquired a 145-megawatt wind farm, it realized the turbines were not yielding as much output as expected due to incorrect setup. Longroad partnered with WindESCo, a US-based renewable energy performance analytics company, which implemented its Swarm System to acquire real-time turbine data, such as angle and energy generated. Data collected by the Swarm System are stored on a cloud server, which feeds into an analytics platform that determines the optimal angles and other turbine settings, optimizing the performance of these assets. As a result, Longroad Energy experienced a 2.5% increase in annual energy production and an annual revenue increase of $430,000.

9. Remote asset monitoring

Remote asset monitoring definition (by IoT Analytics)
Utilizing IoT to monitor assets remotely in a read-only format for performance tracking

Remote asset monitoring drops from most adopted use case while seeing strong growth. Approximately 48% of respondents reported adopting remote asset monitoring, up from 34% in 2021. Interestingly, this use case was the most adopted in 2021. At that time, IoT Analytics noted that remote asset monitoring was the cheapest and easiest to set up due to its simplicity compared to other use cases. With other, more complex use cases surpassing remote asset monitoring while it grew significantly, it becomes even harder to believe that IoT is failing. Rather, companies have realized the benefits of IoT use cases and invested more in them.

Most important KPI affected

The top KPI affected by remote asset monitoring is costs. On average, a major rollout of this use case reduced costs by 6.6%.

Adopter quote

“We have millions of sensors collecting over 5 trillion rows of data that our AI models, combined with our conventional models used to monitor equipment 24 hours a day, 7 days a week, alerting engineers to anomalies from a distance.”

Wael Sawan – CEO, Shell plc, February 01, 2024

10. Location tracking

Location tracking definition (by IoT Analytics)
Employing IoT for real-time location tracking of products/assets/devices

Location tracking is the top connected products use case. Approximately 45% of companies in the survey have adopted location tracking. It is also the only connected product use case to make this list of top 10 IoT use cases. IoT location can be applied across various environments, including warehouses, factories, and outdoor work sites. The location data gathered from the machines or devices help companies locate their equipment and personnel, optimize routing, improve asset utilization, and enhance safety. Tracking the location of an asset can also be beneficial to both the vendor of the products (e.g., by understanding usage patterns) and to the user (e.g., by finding a lost item or by mitigating theft).

Most important KPI affected

The top KPI that is affected by location tracking is revenue. On average, a major rollout of this use case improves revenue of the company selling the connected product by 1.6%.

Additional insights from the IoT Use Case Adoption Report 2024
The report shares the top KPIs that respondents’ companies use to measure the success of their IoT strategies by industry. Zooming in on the energy sector as an example, 88% of energy companies, on average, put high importance on decreasing the average time it takes to detect cybersecurity incidents.

Note: This article was updated in September 2024 to include the latest market data and insights from IoT Analytics.

Article written by Philipp Wegner on October 13, 2021.

The 10 most adopted IoT Use Cases 2021

Six of the top 10 IoT use cases today (ranked by adoption) aim at making operations smart, thus improving companies’ production processes for manufacturing, enhancing maintenance operations, or advancing any other operations (e.g., energy generation in the case of an energy company, running healthcare operations in the case of a hospital, or running store operations in the case of a retail company). Three of the top 10 use cases are related to smart supply chains, and only one is related to smart products in the field.

Here are the 10 most adopted use cases, ranked by their adoption rate:

1. Read-only Remote Asset Monitoring

Not surprisingly, the simplest IoT use case is also the most adopted. Read-only remote asset monitoring refers to assets that are connected from afar in a read-only manner (i.e., one can visualize the asset data, but one cannot send back any commands to the asset itself). This use case is one of the easiest and cheapest to set up due to its simplicity. In many cases, remote asset monitoring supersedes the error-prone and costly manual task of checking and documenting asset states in person. Adoption in 2020 was clearly accelerated by the pandemic and is expected to grow even further, as 36% of interviewees say they plan to invest significantly in this use case in the next two years.

Adopter’s quote

“In the future, our engineers and plant operations staff will not need to sit in cars to go from their office location to another sub-station or satellite equipment room to perform daily routine activities. Routine read-only activities could be done more frequently, which could indirectly contribute to the reliability of control systems.”

Senior operations manager of a mining company in Qatar

Implementation example

Hindustan Coca-Cola Beverages Pvt. Ltd., located near Pune, India, adopted remote asset monitoring for its PET and can-bottling lines. Thttps://aiplindia.com/case-study/he real-time and continuous monitoring of critical parameters (e.g., syrup flow rate, can-rinse pressure, and water temperature) replaced its MS Excel-based manual reporting. In this specific case, the company combined the remote connectivity of its assets with a condition-monitoring use case that generates alarms based on predefined conditions.

| Use case definition (by IoT Analytics)

Remote Asset Monitoring (read-only) = Real-time, one-way data streaming from machinery/equipment to an offsite location (e.g., cloud), making data accessible from anywhere.

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2. IoT-based Process Automation

IoT-based process automation has been rolled out by 33% of companies. This type of process automation describes operational processes that were either entirely manual in the past or relied on antiquated, industrial-automation setups but have now been upgraded with state-of-the-art hardware and software. Companies that introduce this use case to upgrade their existing setups often do so to add flexibility and agility in the operations process so that specific process steps can be changed in the future. This becomes important because companies are increasingly interested in aligning their manufacturing and operations processes to ever-changing customer demands.

Adopter’s quote

“Our manufacturing processes used to have many paper-based steps involved. IoT process automation has reduced many of these paper-based processes, resulting in a reduction in the number of errors, labour cost and real-time access to data.”

CIO of a food and beverage manufacturer in Canada

Implementation example

An Australian farmer, reported he was able to use 20% less water thanks to a new IoT-based irrigation system supplied by Lindsay, a US-based manufacturer of pivot-irrigation systems. Farmers increasingly adopt smart IoT-based irrigation systems to automate the process of irrigation and thereby enhance their crop yields.

| Use case definition (by IoT Analytics)

IoT-based Process Automation = The use of real-time data from connected assets to improve an entire operational process (e.g., a manufacturing process).

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3. Remote Asset Monitoring and Control (read/write)

“Read/Write remote asset monitoring and control” is the extension of “Read-only remote asset monitoring.” On top of “reading” the assets data, with this setup one can also communicate back and thereby influence asset control from afar (i.e., “writing” data back).

Just like the read-only asset monitoring use case, this use case was accelerated by the COVID-19 pandemic as service teams, engineers, and other staff needed to find ways to reach an asset that needed their attention while being in a different location.

Because of the added complexity and security risk of controlling an asset, on top of just simply monitoring, this use case comes with significantly higher costs of installation and maintenance. However, it has been proven that such solutions pay off in a relatively short time: Of those decision makers whom IoT Analytics interviewed, 51% reported amortization in less than 24 months.

Adopter’s quote

“Remote monitoring and control of freezers has saved costly materials before being ruined.”

Research and development (R&D) manager of a manufacturing company in UK

Implementation example

Schlumberger, an oilfield service company, recently adopted a monitoring and control solution from Advantech and ReStream. These companies had partnered up to supply and develop a new oilfield fluid-monitoring system based on LTE connectivity. The project helped to achieve flow assurance, ensure asset integrity, and optimize production. It also helped to increase labor safety. Oilfield companies suffer from a dynamic chemical environment that, if unchecked, can lead to premature wear, lost productivity, and the release of lethal poisonous gases.

| Use case definition (by IoT Analytics)

Remote Asset Monitoring and Control (read/write) = Real-time, two-way data streaming of machinery/equipment from/to an offsite location, enabling data access and the sending of commands from anywhere.

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4. Vehicle Fleet Management (track/trace)

The management of vehicles in a fleet is the number one IoT supply chain use case right now. The larger the fleet of trucks (or other means of transport) to manage, the higher the complexity. Cross-border fleet management can be especially overwhelming, which is why 31% of companies have rolled out a professional vehicle fleet management solution to gather real-time information.

Today, most fleet management solutions are reliant on wide-area connectivity, such as cellular (2G, 3G, 4G). Several new, low-cost IoT satellite technologies have recently been launched and promise to add another option to this use case so that vehicle fleets are always truly connected at a reasonable price. New companies include Hiber (IoT-focused satellite network) and Starlink (part of SpaceX). Both plan to send thousands of new satellites into space in the coming years to provide low-latency, high-bandwidth connectivity globally.

Adopter’s quote

“Now we know virtually in real time where our wagons are located, which routes we can optimize, and where there is potential for savings for our customers.”

Suzy Verachten, project leader, Lineas (European Rail Freight Operator)

Implementation example

Lineas, the largest private rail freight operator in Europe, managed to increase capacity utilization of its fleet by more than 40 percent by implementing the Bosch fleet management solution.

| Use case definition (by IoT Analytics)

Vehicle Fleet Management (track/trace) = Tracking and tracing the location of individual vehicles either on site while in transit or as general fleet management.

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5. Location Tracking (e.g., GPS)

Not every company sells smart-connected IoT products, but of those that do, tracking the location of the asset is the number one use case (31% of companies in our interview set have adopted it). The results from this interview series are in line with results from the IoT Commercialization & Business Model Report 2020, which found that geolocalization was also the number one use case in terms of customer adoption when original equipment manufacturers (OEMs) were asked which smart product features their end customers were adopting as part of their IoT-enabled assets. Location tracking is therefore important for developing a successful IoT business model.

Tracking the location of an asset can be beneficial to both the vendor of the products (e.g., by understanding usage patterns) and to the user (e.g., by finding a lost item or by mitigating theft).

Adopter’s quote

“Connectivity means we can monitor distance covered, send service alerts, or lock the bike remotely. Things become even more interesting when we mesh this data with other transport data. If we can map the routes of thousands of cyclists, could we help urban planners develop better cycling infrastructure?”

Taco Carlier, co-founder, VanMoof

Implementation example

VanMoof, an Amsterdam-based e-bike manufacturer, offers an anti-theft service to its customers that is based on the location tracking of a bike. For a monthly fee, the company sends its “bike hunters” if a customer’s bike is stolen. The bikes are connected and tracked by a combination of Bluetooth and cellular networks. This allows the company to keep its promise of recovering the bike in up to 70% of cases.

| Use case definition (by IoT Analytics)

Location Tracking (e.g., GPS) = Tracking product location to determine its movement and geographic position.

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6. IoT for Asset/Plant Performance Optimization

Asset performance management (APM) is a term in manufacturing to describe methods of capturing and integrating data, visualizing it, and analyzing it to improve the reliability and availability of physical plant–floor assets. IoT for asset/plant performance optimization is the modern version of APM. It integrates state-of-the-art data-capture and integration tools (like IoT gateways) and software tools (like IoT platforms) to analyze how assets can be run and maintained at optimum levels (e.g., optimized asset speed settings, optimized material input settings, or optimized maintenance intervals).

More than 30% of companies in our interview set have adopted IoT for asset/plant performance optimization. With 42% of companies planning to invest significantly in IoT for this purpose, it is among the use cases with the highest expected growth rate.

Adopter’s quote

“The use of IoT for plant performance optimization has been a success since it now allows us to run our CHP power utilities at optimal levels based on variable fuel mix and plant loads for steam and power.”

CEO, manufacturing: chemicals and chemical products, India

Implementation example

A beverage manufacturer that was running mostly older equipment used an IoT solution provided by Relayr in one of its bottling plants, which produces 1.2 million bottles per day per production line. It achieved improvements of 11% in performance and 8% in quality. Implementing an IoT retrofit kit and an IoT gateway, the company was able to identify the processes responsible for 90% of the plant’s downtime. Based on the IoT data collected from the legacy machinery of different manufacturers, the company was able to address several issues (e.g., changing the control logic of the machines).

| Use case definition (by IoT Analytics)

IoT for Asset/Plant Performance Optimization = The use of real-time data from connected assets to optimize individual asset health for better operations performance at a site.

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7. IoT- based Quality Control & Management

IoT-based quality control and management involves the use of machine vision or other IoT sensor data to detect quality issues in real time during operations. The use case pays off particularly quickly: Of the 30% of companies that have implemented this IoT use case, two-thirds report amortization in fewer than 24 months.

Adopter’s quote

“We can now tell quickly if the environmental parameters are not quite right at some point, either within the paint shop or in one of the buffer areas. It takes a lot of data to do this, which we collect throughout the process, evaluate historically and analyse in real time”

Martin Hilt, innovation and digitalization officer at BMW

Implementation example

A leading global automobile manufacturer automated the testing of the electronic functionality of its cars during the manufacturing process. As the company was adding greater electronic functionality to the cars to stay current with technological developments, it was looking to find ways to optimize its time-consuming, manual method of checking the operation of electronic parts. With the help of Cognizant, the company was able to completely automate vehicle testing and also implement a mixed-mode validation to simulate missing parts that would arrive late due to unforeseen supply chain issues. The solution realized a positive return on investment in four months.

| Use case definition (by IoT Analytics)

IoT- based Quality Control & Management = The use of IoT sensor data or machine vision to monitor operational process parameters and detect faults (in real time) with the goal of reducing scrap/rework.

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8. IoT-based goods condition monitoring in transit

Monitoring the conditions of goods is essential in industries such as pharmaceuticals or food and beverage and can even be seen as a way to help tackle the global food shortage. Temperature sensor data is one of the most important sensor values for this use case; it guarantees the safety of the final product by close monitoring throughout the entire supply chain, both in transit and in storage.

Condition-monitoring solutions were used by 29% of the interviewed decision makers as part of their digital supply chain initiatives.

Adopter’s quote

“The assessment [of goods in transit] was an eye-opener, because we never looked at supply chain risk holistically before. Now we know where the risks are.”

An D’haenens, logistics manager EMEA, DuPont

Implementation example

A global life sciences company worked with DHL to enable pallets with smart sensors. The sensors are equipped with low-power wide-area (LPWA) connectivity and track geographic location, movement, delay, shock, and temperature. This ability has enabled the life science company to reduce its life-cycle costs by 6 to 7%, with reported reliability of nearly 100%.

| Use case definition (by IoT Analytics)

IoT-based goods condition monitoring in transit = The use of IoT sensor data to monitor the condition of transported goods and ensure they remain safe and are not exposed to the wrong temperatures or shocks.

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9. Predictive Maintenance

To forecast the remaining useful life of assets and ensure they are repaired before they fail, 29% of all companies have invested in solutions at the intersection of artificial intelligence and maintenance. As IoT Analytics highlighted in a recent blog post, predictive maintenance (PdM) is an en vogue topic, with 40% of interviewed decision makers planning to invest significant amounts of money in the coming two years.

Adopter’s quote

“PdM enabled us to actively monitor highly critical assets, provided us with multiple feeds of various data points (temp, vibration, throughput), allowed [us] to perform analysis of the asset health in real time, and helped us to prevent the need [for] reactive maintenance actions for critical assets.”

IT director at an Oil&Gas company in the United States

Implementation example

Colgate-Palmolive Company, a US-based consumer goods manufacturer, leveraged a predictive maintenance solution to optimize its manufacturing capacity and prevent costly downtime. It installed wireless sensors on 2,000 machines (including tube makers and liquid machines) to collect machine data. The predictive maintenance solution detected increased temperatures and alerted staff, thereby preventing nearly 200 hours of downtime and a missing output of 2.8 million tubes of toothpaste.

| Use case definition (by IoT Analytics)

Predictive Maintenance = The use of real-time IoT sensor data and artificial intelligence (AI) techniques to determine when maintenance should be performed on specific equipment.

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10. On-Site Track and Trace

The availability of low-cost sensors and trackers has made it easy and relatively cheap to track goods and tools at construction sites, ports, and even inside buildings (e.g., factories). Of the experts interviewed, 29% have implemented such a solution. The median spending for a fully functional, on-site track-and-trace solution (in our interview set) is only $25,000—one of the lowest in the data set. Costs can scale up, however, as more and more assets get connected.

Adopter’s quote

“Having On-Site Track & Trace has improved our efficiency [and] reduced labor time for tracking items (we have almost 1,000 stock-keeping units). We are now also able to check stock balances in real time.”

Head of IT at a retailer in Singapore

Implementation example

Continental, a German automotive supplier, implemented KINEXON’S real-time locating solution at its logistics center and production site in Regensburg. More than 50 transportation vehicles and more than 3,000 load carriers are tracked live inside the 30,000 m² building sites, allowing Continental to locate each of these items within a precision of several centimeters (inches), thereby creating a transparent material flow in the supply chain and increasing overall throughput.

| Use case definition (by IoT Analytics)

On-Site Track and Trace = Tracking and tracing goods while on site (e.g., at production sites, ports, logistics centers, or warehouses).

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The IoT Use Case Adoption Report 2024 is a 418-page report on the adoption, spending, ROI, future investments for use cases in smart operations, supply chain and connected products. Based on insights from 200 IoT adopters across various verticals, regions, company sizes

This report provides answers to the following questions (among others):

• What are the most adopted IoT use cases (out of a list of 27)?
• Which IoT use cases have the highest return on investment (ROI)?
• Which KPIs are most important for a company’s IoT strategy, and how are the KPIs affected by implementing IoT use cases?
• How much do companies spend on hardware, software, and services for individual IoT use cases?
• Which IoT use cases do companies plan to invest in the most in 2024?
• Who are the leading vendors for IoT use cases, how satisfied are end users, and what are the strengths and weaknesses of the top vendors?
• What challenges do IoT end users face when implementing use cases?
• How do companies ensure their workforce has the necessary IoT skills?
• How much are companies’ IoT strategies impacting their sustainability goals?

Related publications

You may be interested in the following publications:

• IoT Use Case Adoption Report 2024
• State of IoT Summer 2024
• IoT Startup Landscape and Database 2024
• IoT Enterprise Projects Adoption Report 2024

Related market data

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• Global IoT Enterprise Spending

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• State of IoT 2024: Number of connected IoT devices growing 13% to 18.8 billion globally
• IoT Startup Landscape 2024: 7 notable insights
• IoT market update: Enterprise IoT market size reached $269 billion in 2023, with growth deceleration in 2024
• Top 5 enterprise technology priorities: AI on the rise, but cybersecurity remains on top

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