Edge computing brings cloud resources (compute, networking, storage) closer to applications, devices and users.
In order for edge computing to be widely adopted by businesses around the world, it will take a commitment from these large companies to build out a massive distributed network. A new market must be established beyond telcos and content studios, where the demand for edge computing and analytics in real-time justifies the investment by large enterprises.
As this new technology becomes widely adapted, it is important to understand how it will be used to improve our day-to-day lives today and in the near future. With this in mind, here is our list of the Top 10 Edge Computing use cases:
1. Autonomous Vehicles
With the adoption of self-driving cars such as Tesla leading the way, the future of autonomous vehicles has also extended to long-haul trucking and farming tractors in rural areas. These sophisticated smart vehicles can generate upwards of 5TB of data per day, and require massive on-board processing power to reach true autonomy.
Luxury car markers such as Mercedes-Benz are now catching up with the latest technology, with the recent announcement of “Level 3” autonomy which allows drivers to take their hands off the wheel for extended periods of time thanks to advanced sensors and mapping technology that come equipped in each vehicle.
2. Artificial Intelligence
AI is quickly becoming more advanced and increasingly adopted by the modern world in a variety of industries which are all included in this list. We now have the ability to make services and devices smarter by increasing the processing power in smartphones and edge devices.
As more and more data is produced, it will be offloaded to local edge devices for processing instead of directly to the cloud. With AI becoming more powerful and widely distributed, new edge use cases will emerge, leading to increased real-time analytics and reduced labor costs for businesses.
3. IoT
IoT-enabled devices have made edge computing architecture a necessity for enterprise companies around the world. While machine-to-machine communication and connected devices have been around for several years, today’s IoT has evolved due to the number of devices and the amount of data they are sending over networks. Edge computing cuts down latency from these devices by processing the data locally where it occurs.
4. Content Delivery
With movie theaters looking more and more like a thing of the past, people are flocking to streaming services such as Netflix, Disney+ and YouTube to deliver streaming content at scale.
With 4k and HD video quickly becoming the standard for viewer consumption, CDN’s will need to beef up their infrastructure to deliver an incredible variety of content including audio streams, software downloads, mobile apps and games.
5. 5G Infrastructure
By 2023, 5G will make up nearly one-fifth of all mobile data traffic, where 25% of the use-cases will depend on edge computing capabilities. The current gap in carrier testing and mainstream adoption will be the availability of devices with 5G and the hardware and software to support it.
6. Video Gaming
When it comes to video gaming, the most important thing to the end user is low-latency since many of today’s games are happening online with players from all over the world. With the holiday releases of both the Sony Playstation 5 and Xbox Series next-gen consoles keeping people busy at home, reducing lag is priority number one.
7. TV and Film Production
As more streaming services like Netflix and Amazon become content producers, they must look for ways to revamp the on-location film production in which couriers are used to deliver the raw and unedited footage shot during the day. Many of these studios see edge computing as a way to accelerate this manual process.
8. Factory Automation
Industrial cities and towns across the country have little to no data center infrastructure in place. This will soon need to change with the rise of automation on factory floors, where large amounts of data with potential business value is being generated.
9. Telehealth Services
The rise of virtual doctor appointments has increased sharply since the pandemic, quickly shifting from an option to a necessity for doctors and patients alike. These virtual telehealth services will require more local infrastructure over time as they integrate high-resolution medical imaging like CAT scans and X-Rays.
10. VR/AR
Although VR has yet to catch on with a mainstream audience, edge computing capacity can reduce latency in a way that will make it more VR and AR more accessible to a mainstream audience. This will make the experience more enjoyable by reducing motion-sickness due to lag.