8 minutes
Few modern technologies have captured the collective imagination quite like the recent development of the Internet of Things (IoT). The term, invented in 1999 by innovator Kevin Ashton, describes a vast, interconnected world of objects that share information through the internet, enabling connected devices to perform tasks autonomously.1
Today, thanks to the spread of 5G technology, IoT devices are everywhere. From vehicles and household appliances to drones, satellites and even entire manufacturing plants, embedded sensors collect and share data over lightning-fast networks, enabling cutting-edge technologies such as artificial intelligence (AI) and cloud computing to flourish. According to Forbes, the number of IoT devices has more than doubled in recent years, from 10.3 billion in 2018 to 25 billion in 2025.2
However, underpinning the performance of many IoT applications is an ocean of big data that companies need to collect and store safely for the applications to function. From fully automated manufacturing facilities to smarter cities and energy grids, IoT devices generate more data than companies know what to do with.
Enter edge computing, a technology that gives enterprises greater flexibility in how they process data generated by IoT devices. Edge computing is a distributed computing framework that enables data to be processed closer to its source—at “the edge” of the speedy networks data travels across. This reduces latency and bandwidth issues that are common when IoT data is processed in centralized data centers.
The term ‘big data’ describes information companies gather from various sources, including social media, the internet and databases. Technically, IoT data is a subset of big data that deals only with information gathered from a device connected to an IoT network, such as a sensor or meter. However, IoT data is different from other types of data in three important ways and must be handled accordingly.
IoT data is generated by a device that’s connected to the internet. Big data, however, can be generated by several sources—for example, a users’ social media history, financial transactions and more. This means that IoT data is often tightly structured and formatted, bound by the constraints of the devices delivering the information, such as a meter or sensor. Big data, however, is typically unstructured.
Data centers designed to process large, unstructured datasets are often not up to the task of processing data continuously—a core requirement of most IoT applications—which can lead to latency and accuracy issues.
The growing number of connected IoT devices generates a staggering amount of data. According to a recent study, IoT devices generated 86 petabytes of information in 2022 and will generate more than 1,100 by 2027—a growth rate of more than 1,000%.3
Traditional data centers are not built for this volume of data, especially when it's being transmitted continuously the way IoT devices are designed. The deluge of data fills up their storage systems and causes problems.
IoT data is sent real-time and needs to be processed immediately for the applications it powers to be effective. Imagine if a self-driving car had to wait for data regarding traffic lights to be processed in a data center and sent back before it can react. Big data often includes historical data that can be processed in batches, over time, without affecting the performance of associated applications.
Traditional data centers—physical, on-premise buildings that house IT infrastructure—were designed to store and process large, unstructured data volumes in batches, over time. While this architecture might be optimal for large-scale, complex data processing, it is less than ideal for the volume, scale and real-time needs of IoT workloads.
The number and complexity of data sources IoT technology relies on—coupled with the amount of data and the speeds at which the devices transmit it—often overwhelms traditional data centers. Edge computing and so-called ‘edge data centers,’ store and process data in ways that make it a better fit.
Edge solutions offer a compelling alternative to traditional data center models for IoT devices. Unlike traditional data processing methods, one of the benefits of edge computing is that data can be processed and analyzed as it is received. It is even close to the point where it is being generated rather than being sent to the cloud or a traditional database.
With an edge solution, data generated by an IoT device can be processed and analyzed in real-time by a nonrelational database (NoSQL) application, located at the edge of the network. For example, in the case of driverless cars, edge computing is critical in providing real-time reaction capabilities to avoid a collision.
This approach is used—with slight differences in design depending on the device—across many IoT applications, helping reduce network congestion and enable real-time response capabilities. However, even with these enhanced edge solutions, IoT devices still collect more data than they need to function
Because IoT devices only use a small fraction of the amount of data they generate, some businesses decide to discard any additional data. On the surface, this would appear to be a relatively simple solution, but IoT data isn’t like garbage that can be bagged up and taken to the curb. IoT devices exist in homes, cars and other private spaces and often contain highly personal and heavily regulated information.
In addition to detecting wind speed or the color of a traffic light, for example, an IoT device can generate volumes of personally identifiable information (PII). Some examples are: an individual’s location, financial history, internet usage and more. This data must be collected, stored and analyzed in compliance with rigorous data sovereignty laws that are expensive to violate.
So, if data collected by IoT devices must be stored securely, how can businesses put it to use to generate insights and serve some larger business purpose?
The potential use cases for data generated by IoT-connected devices are staggering. According to a recent report, the data generated by IoT devices is poised to unleash between USD 5.5 and 12.6 trillion in value over the next 5 years.4
When it is safely stored and processed in compliance with all relevant, local laws, data generated by IoT devices can help companies find insights, discover trends, plan future products and more. Here are five areas where modern enterprises are putting IoT data to use.
IoT devices such as smart refrigerators, autonomous cars and smart-home energy sensors help customers automate processes that previously required manual input. But they can also generate valuable insights into customer behavior, preferences and even help companies plan new products.
Using the data generated by a smart refrigerator, for example, a company can learn which products a customer prefers and either sell that information on to a third party or use it to market more services to them.
Edge computing holds tremendous potential for the ways farmers choose which crops to plant, how they harvest them and how they plan for changing weather conditions.
Using real-time information from sensors embedded in soil and crops, they can more effectively manage growth and fertilizers, and spot potential threats such as infestations. Ranchers managing herds of livestock are turning to edge computing to monitor animals remotely and detect early signs of disease.
Smart monitoring systems in industrial plants embed hundreds of IoT devices with sensors that provide information on temperature, operational efficiency, speed and more. While these systems help automate processes that previously required human intervention, they also generate data that can be used in other ways.
In the field of predictive maintenance, for example, companies are using IoT data to better plan for downtime and keep their most valuable assets operating at peak efficiency. Information from sensors in the machines accurately predicts when certain components fail, informing maintenance practices and helping managers schedule repairs during off-peak usage times.
Smart devices in the healthcare industry—such as watches that monitor heart rate, blood glucose and more—are helping improve care and outcomes for patients suffering from various ailments. Like in other industries, the devices gather more information from a patient than is necessary for the IoT device to function.
For example, in the case of a patient who uses a wearable device to track heart rate, they can opt in to a service that uses the device data to recommend dietary supplements or workout routines informed by other information gathered by the wearable.
IoT devices such as cameras and movement sensors connected to a network are dramatically impacting the security industry. New IoT devices reduce the risk for operators and security personnel and sometimes make in-person patrols unnecessary.
Also, though, the information generated by these devices is leading to improvements in the way security companies provide their services. Information gathered by these cameras and other sensors, for example, can be analyzed to predict threats, identify patterns and design more proactive responses.
IoT devices generate more data than companies know what to do with, but with 5G wireless connectivity and edge computing, they are discovering new applications for it.
Today, IoT devices are virtually everywhere, collecting information from a wide range of devices, including household appliances, driverless vehicles, satellites and many, many more. Processing data at the edge and in real-time, rather than moving it to servers as it was done in the past, is paving the way for the development of groundbreaking new applications.
From smarter factories and cities to IoT-enabled healthcare solutions and remote facility and equipment monitoring, the number of enterprise IoT and edge computing applications is growing rapidly. By investing in edge computing and IoT, enterprises can speed digital transformation, help uncover new insights into processes and allow themselves to act immediately on live data.
All links reside outside IBM.
1 Kevin Ashton describes the ‘Internet of Things’, Smithsonian Magazine, January 2015
2 Connecting the dots: The future of IoT in the Enterprise, Forbes, July 2024
3 Roaming IoT Connections to Generate 1,100 Petabytes Globally by 2027, Juniper Research, August 2022
4 IoT Value set to accelerate through 2030, McKinsey, November 2021
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