1. Autonomous Vehicles
Autonomous grouping of truck convoys may be one of the first use cases for autonomous vehicles. Here, a group of trucks traveling right behind each other in a convoy saves on fuel costs and reduces congestion. With edge computing, all trucks except the one in front will no longer need a driver because the trucks will be able to communicate with each other with ultra-low latency.
2. Remote monitoring of assets in the oil and gas industry
Failures in oil and gas can be catastrophic. Therefore, their assets need to be carefully monitored.
However, oil and gas plants are often located in remote areas. Edge computing brings real-time analytics and processing closer to the assets, which means less reliance on high-quality connectivity to a centralized cloud.
3. Smart Grid
Edge computing will be a core technology in the wider adoption of the smart grid, helping organizations better manage their energy consumption.
Sensors and IoT devices connected to edge platforms in factories, plants and offices are being used to monitor energy use and analyze its consumption in real time. With real-time visibility, businesses and energy companies can strike new deals, such as running high-powered machinery during off-peak hours of power demand. This could increase businesses' consumption of green energy, such as wind power.
4. Predictive maintenance
Manufacturers want to be able to analyze and detect changes in their production lines before failures occur.
Edge computing helps bring the processing and storage of data closer to the device. This enables IoT sensors to monitor machine health with low latency and perform analytics in real time.
5. Inpatient monitoring
Healthcare contains several edge opportunities. Currently, monitoring devices, such as glucose monitors, wellness tools and other sensors, are either unconnected or require large amounts of unprocessed data from the device to be stored on a third-party cloud. This creates security issues for healthcare providers.
The edge on hospital sites can process data locally to protect data privacy. Edge computing can also provide practitioners with timely notification of unusual patient trends or behaviors.
6. Cloud gaming
Cloud gaming is a new type of gaming that delivers real-time content from games, which are highly latency-dependent, directly to the device.
Cloud gaming companies are looking for edge servers as close to the player as possible to minimize latency and provide a fully responsive and immersive gaming experience.
7. Content Delivery
Content delivery can be dramatically improved by caching content, such as music, video streams, web pages, etc., at the edge. Latency can be significantly reduced. Content providers are looking for broader distribution CDNs, thus ensuring network flexibility and customization based on user traffic demands.
8. Traffic management
Edge computing can make urban traffic management more effective. Examples include optimizing transit frequencies in the face of fluctuating demand, managing the opening and closing of additional lanes, and managing self-driving car traffic in the future.
With edge computing, bringing processing and storage closer to the smart home reduces backhaul and round-trip times and handles sensitive information at the edge. For example, voice assistant devices such as Amazon's Alexa will have much faster response times.
With edge computing, there is no need to transfer large amounts of traffic data to a centralized cloud, reducing the cost of bandwidth and latency.
9. Smart home
Smart homes rely on IoT devices to collect and process data from around the house. Typically, this data is sent to a centralized remote server where it is processed and stored. However, this existing architecture suffers from backhaul costs, latency and security concerns.
With edge computing, processing and storage are brought closer to the smart home, reducing round-trip time and processing sensitive information at the edge.
These are just a few of the many use cases that edge computing supports across multiple industries. In terms of Harmony Cloud's edge computing application examples, in the communications field, Harmony Cloud custom developed and built a cloud edge collaboration platform for the business scenarios of an online service company, a giant in the industry, to help it easily cope with traffic peaks; in the transportation field, Harmony Cloud joined forces with SAIC's Commercial Vehicle Technology Center to build the "next-generation, container-based vehicle-cloud collaboration architecture," the first "container-based vehicle-cloud collaboration architecture" in the automotive industry. In the field of transportation, we jointly built the "container-based next-generation vehicle cloud collaboration architecture" with the Commercial Vehicle Technology Center of SAIC Group, which is the first "cloud, edge, and end" integrated architecture in the automotive industry, and can realize the large-scale access of million-level vehicle networking; and we have built an integrated collaboration product for a cross-sea bridge, accumulated rich experience in the docking of "edge-end" equipment protocols, and delivered the industry's top-notch "software and hardware integration" platform. The company has accumulated rich experience in "side-to-end" device protocol docking, and delivered the industry's top "software-hardware integration" total solution.
An online service company and SAIC case won the "Top 10 Practice Cases of Distributed Cloud and Cloud-Edge Collaboration in 2020" and "Top 10 Practice Cases of Distributed Cloud and Cloud-Edge Collaboration in 2021" awards, respectively. Its edge computing products passed the "2021 Cloud Edge Collaboration Category Capability Assessment", "Edge All-in-One Machine, Trustworthy IoT Cloud Platform (General/Security Requirements)", and were awarded the Zhejiang CCF2021 Outstanding Product Award, and have an excellent reputation and have been recognized by industry authorities. It has an excellent reputation in the industry and has been recognized by the industry authority.
Currently, Harmony Cloud edge computing has been practiced in multiple scenarios such as distributed cloud, IoT, vehicle-cloud collaboration, and edge intelligent finance, setting up practice benchmarks and classic cases in the field of edge computing. And in some typical industries such as communications, transportation, finance, military and many other industries in the field of large-scale landing verification.