Just as global industries continue to embrace cloud-native IT infrastructure, edge computing is becoming an innovative and intelligent means of connecting their IT and physical resources. That’s because edge computing brings intelligence right to endpoint devices, rather than relying solely on centralized enterprise resources. Its growing sophistication and relevance are driven by growth in 5G, artificial intelligence, augmented reality, and other next-generation technologies, where business leaders increasingly see value in high-power computing that happens at the edge.

 

As a result, the global edge computing market is expected to increase from $3.5 billion in 2019 to more than $43 billion in 2027, Forbes reports. Internet of Things (IoT) sensors, video cameras, mobile devices, and augmented reality headsets are all candidates for edge computing, where practical use cases—those that drive real business benefits—are now beginning to emerge. In this article, we’ll take a realistic look at edge computing’s potential, including the reasons for its market growth and several business use cases where edge computing is proving effective.

 

Why Edge Computing Matters

 

We can define edge computing as comprising one part of a distributed network; a segment that features information processing at that network’s “edge.” Specifically, edge computing happens at endpoint devices as opposed to centralized IT resources, even though the two are often connected via high-speed connectivity.

 

Edge computing as we understand it today is a trend whereby companies increasingly shift processing power “closer” to the edge of a given network. “That means the data is used before it even crosses the WAN [wide area network],” as Forbes describes. Shifting compute workloads closer to the edge means quicker results local users and systems of those edge devices; it reduces labor for centralized resources that communicate with the edge on a more efficient, “as needed” basis as well.

 

In today’s distributed world, there are near endless applications for modern edge computing. Mobile apps, IoT sensors in manufacturing facilities, and automated vehicles are all candidates. This is especially true in use cases where some central connectivity is necessary, but end users need real-time results.

 

The “Edge” Has Real Business Potential

 

Recent advances and the growing affordability of core technologies make modern applications for edge computing more viable. Computing power has dropped in price by roughly 57%, McKinsey reports, as have prices for IoT sensors (~44% drop) and data storage (~72%). When these cost-effective resources are applied to edge devices, they make high performance at the edge possible; this can drive up overall network performance exponentially, and make new types of digital capabilities possible.

 

For example, IoT devices are already producing data at unprecedented rates. Due to delays between remote readings and processing via centralized IT resources, much of that data is discarded or ignored. Edge computing enables companies to process that data faster and closer to the point of data collection.

 

Edge computing can deliver unprecedented results to human users “close” to edge compute resources as well. For example, consumer mobile apps do more computing via local resources or even on the user’s device itself rather than through data exchanges with the cloud. Near real-time processing provides a faster, more robust user experience, and opens doors for all types of new capabilities (e.g., high-performance augmented reality).

 

10 Modern Use Cases for Edge Computing

 

Now that we have a conceptional understanding of edge computing, we can take a look at real use cases where edge computing is driving business results today. Consider the following examples of edge computing in action as you determine what adopting modern edge computing might mean for your own organization.

 

1. Distributed Enterprise Workloads

 

Enterprise companies can effectively run enterprise workloads at distributed and colocation data centers as well as other types of external infrastructure. Companies that use colocation facilities can distribute more IT functions to those locations, for example; they can quickly shift functions between infrastructure to meet changing business demands as well.

 

2. Customer User Experiences

 

Companies can move compute resources closer to customers, ensuring faster response times and more robust capabilities on devices that represent end-user touchpoints (e.g., their mobile devices). Edge computing can enhance the performance of online gaming and video streaming, for example, where applications leverage nearby edge computing resources in delivering those experiences. Companies can optimize and better protect customers’ personal data by isolating sensitive information to edge resources, thereby minimizing risk.

 

3. In-Store Retail Environments

 

Any number of endpoint devices within a physical retail location can be enhanced by edge computing. These might include RFID tags on merchandise, in-store surveillance cameras, POS systems, and others. Interactive in-store devices like kiosks or even augmented reality can do more for customers faster, or function at near-full capacity when internet connectivity is lost. Enterprise retailers can process more robust analytics at the level of individual stores as well.

 

4. Video Surveillance and Processing

 

Recorded video is among the most data-heavy assets and requires lots of computing power to process and analyze. Edge resources can do much of this work closer to where that video is recorded before communicating with centralized IT resources. For networks with a wide range of surveillance resources, this can dramatically reduce the time it takes to store and analyze data from surveillance footage, and also allow for greater sophistication in terms of those processes.

 

5. Patient Monitoring and Analytics

 

Healthcare institutions generate vast amounts of sensitive data, even in traditional settings. The amount of data produced by healthcare and life sciences fields has gone up by nearly 900% in the past two years, Forbes reports, “due to things like wearables and other connected devices.” Edging computing makes processing this data easier and faster, allowing healthcare professionals to access robust data in near-real time.

 

In healthcare logistics, edge computing can enhance real-time monitoring of shipping containers where merchandise has very specific requirements (e.g., temperature). Edge computing can greatly improve remote healthcare settings such as in rural areas as well, where deeper analytics and more robust patient monitoring are possible.

 

6. Manufacturing and Industrial Processes

 

Factories and other industrial facilities have hundreds of thousands of touchpoints, each of which can produce vast amounts of data about performance, equipment status, and efficiency opportunities, among other factors. Industry leaders have begun using IoT sensors to capture that data, but processing it all is cumbersome. Edge computing means operations leaders can monitor thousands of touchpoints and analyze much of that data at the edge, driving insights that improve employee productivity, reduce downtime, and reveal opportunities for greater performance at and across locations.

 

7. Enhanced Augmented Reality

 

Whether it’s used for entertainment or business functions, augmented reality (AR) is growing more common as an end-user technology. Edge computing means AR users can do more with their individual AR devices—enhanced visual or sensory experiences, for example, as well as data capture and analysis.

 

8. Smart Buildings

 

Enterprise companies with dozens of office locations can optimize facility management and employee experiences by pushing compute power to the edge. On-location leaders can make improvements to a wide variety of building functions as a result—including energy usage, planned IT downtime, maintaining telecommunications equipment, and others.

 

9. Autonomous Vehicles

 

In a future world where autonomous vehicles are ubiquitous, advanced edge computing is essential. Connected vehicles will employ navigation and video analytics at the edge for real-time routing, steering, and acceleration in vehicles themselves. Vehicles will communicate with one another even as they factor in local weather and traffic patterns when planning and navigating routes, all through computing at the edge.

 

10. 5G and Telecommunications

 

Edge computing in combination with emerging 5G infrastructure will transform the connected world as we know it. As computing at the edge becomes more sophisticated, mobile connectivity becomes faster and stronger so that both elements of distributed computing are becoming astonishingly more robust. “Advancement in cloud and edge computing will increase demand for 5G by driving data-hungry applications,” McKinsey describes, where the number of IoT devices will reach roughly 42 billion by 2025.

 

Start with Business Value

 

For most business leaders, it’s difficult to know where to begin with edge computing. And while companies in the same industries have overlapping needs, the impetus for any particular application will differ from one to the next.

 

Starting with a top-down approach, begin with a small use case that are most likely to yield business value in a short period. That way, you can ensure you have a solid foundation as you look to scale edge computing use cases across your organization.

 

Partner with Uvation for Your Edge Computing Transformation

 

Uvation can help you prepare your own edge computing strategy, so you can secure a competitive advantage starting today. Contact one of our edge computing experts for a free consultation.