Edge computing, quite simply, complements the cloud, inexpensively analyzes and keeps data nearer to the where it’s required the most. As the pace of business intensifies, the expectation for instantaneous response times is critical for a competitive advantage. Primarily functioning as a complement to cloud computing, edge computing utilizes sensors, controllers and other connected devices to collect and analyze IoT data, which is then transmitted to a server or laptop, for initial analysis. Data processing and its analysis closer to the edge or the network is put immediately into action as opposed to the data center or the cloud. In this blog, we elaborate on the additional benefits and industrial applications of edge computing.
What are the advantages of edge computing?
Edge computing facilitates data processing closer to devices like smartphones, sensors, drones, robots, HVAC units, self-driving cars, and other intelligent devices that process data at the edge versus transmitting that data to a central or core processing unit.
Here are some of the key benefits:
- Increases the time value of each data, providing near-instant intelligence
- Provides real-time analytics that impacts the bottom line, by collecting instant data
- Catches a disaster even before it happens, as it processes data before reaching the cloud
- Cut through data bottlenecks and provides fast and actionable insights
Edge computing use cases:
Let’s take a quick look at the industries that edge computing will transform:
Oil and gas: Probably bridging the gap between standard operations and a disaster, edge computing hopes to resolve this for manufacturing and oil and gas operations. The fundamental advantage of having edge computing at your disposal is the ability to update near-instant analysis at the site. Edge computing is highly useful for remote monitoring of oil rigs that are updated as soon as the data is created. An organization can take direct information as soon as there are signs of disaster, to prevent any future catastrophes.
Augmented Reality: The edge computing platform facilitates AR services with the help of localized data, which is specific to the user. Low latency and high rate of data processing are the essentials for augmented reality to provide the correct information, depending on the user location. With the help of drones, humans in remote places can reach each other. Powered by a supercomputer, drones use artificial intelligence to create flight paths for collecting high-definition images of critical infrastructure, automated safety inspections at oil rigs that are located far away, along with additional sensors and cameras to collect essential data and video footage.
Automated vehicles: Tech giants like Google and Uber are significant beneficiaries of edge computing for their self-driving cars. Edge computing will play a crucial role in helping self-driving cars process and transfer critical data in real-time. With this technology, automated vehicles can help save thousands of lives and billions of dollars that are directly related to automobile casualties.
5G technology: With autonomous driving, multiple data-intensive initiatives for smart city, AR/VR type applications, we are mostly moving the ability to compute, store and process power closer to the network’s edge. This is the highlight for delivering 5G use cases.
Rapid organizational transitions and progressively disbursed sources of information has created an urgency to analyze historical data in real-time with social, IoT sensors and other types of streaming data. With these advantages, it’s possible to say that by adopting edge computing, companies will have a competitive advantage.