Regardless of industry, there are universal business needs that exist. Your patient needs timely medical care, your industrial applications need enhanced safety, or your smart factory devices need to communicate efficiently. Simply put, the desire to improve processes and experiences is always present. But how do you decide and design solutions quickly? The short answer is data analysis. The issue is that, by now, we’re tracking more data than we can digest, and some instances call for rapid decision-making, and that's where edge computing comes in. Let’s look at how edge computing applications can improve your work.

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What’s edge computing?

Edge computing refers to computing that processes and stores data close to the data source (closer to the edge!), unlike centralized cloud storage servers, which are far away. For example, data generated from activities within a retail store can be decentralized in processing and storing at a center closer to the location, rather than relying on centralized cloud storage. Edge computing generally complements cloud computing and is unlikely to replace it. This is because not all information generated by devices needs time-sensitive processing, and can continue to use the cloud for data storage. Essentially, edge computing should be able to distinguish between the correct data to retain and data to either move to the cloud or discard. 

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What are the benefits?

As IBM describes, edge computing’s closeness to the source can produce insights quickly, speed up reaction times, and has better bandwidth availability. 

When Edge computing and 5G technology combine, processing speeds are greatly improved, which means several industries that have zero tolerance for lag can use it, like healthcare for robotic surgeries or automobiles and self-driving cars, to name a few. 

The technology offers some major value propositions: lower latency, lower bandwidth usage, better privacy and security, and greater accessibility. 

Explore the Edge Computing industry hub to understand more about the technology, industry performance, and ecosystem. 

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How do these benefits translate?

We’ve seen technology built on technology by converging and/or needing a tech to power it. Similarly, edge computing involves AI and machine learning and becomes a part of a holistic solution—it's a combination of tech. IIoT is a good example where a network of devices that respond to virtual instruction is created, one that demands faster processing speeds closer to the data collection source. It wouldn’t make sense if a machine couldn’t shut down as needed, in real-time! 

Here’s a quick look at use cases where speed is critical. We note that this is not an exhaustive list of use cases, and we refer to, but don’t thoroughly explore, a subset of edge computing solutions called Multi-access Edge Computing (MECs), where the computing and storage take place at the edge of the service provider’s network. It’s the same edge computing technology, but it leverages access to more commonly found centers, such as through base stations, radio nodes, and aggregation points, rather than in traditional infrastructures, like servers in industrial premises, retail stores, and smart homes, etc.

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Emergency response 

When disasters strike, search and rescue teams, as well as victims and respective families, would need to communicate with each other reliably and clearly. MECs are better equipped to handle such situations given better reliability.

Robotic surgery 

For robotic-assisted surgery, a physician needs to control surgical systems to improve precision. On some occasions, the physician may not be present in the same location (telerobotic surgery). In both scenarios, the superior latency and bandwidth of MECs can enable these surgeries as a response delay can be a matter of life or death.

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Autonomous cars

Autonomous cars rely on fast data processing since even slight delays can lead to accidents. Edge computing technology can be used to communicate a range of information on road infrastructure, the position of pedestrians and vehicles, as well as weather conditions, directly to vehicles.

Industrial applications

IIoT and smart factories benefit from faster communication between devices, which can make it safer, save costs (through timely device shutdowns), and give users real-time insights on tools, equipment, machinery, and environmental factors to optimize the use of devices.

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Conclusion

Across industries, having faster processing speeds to optimize tasks is becoming a requirement. Since the data can be processed and analyzed closer to the point where it's created, edge computing— combined with the cloud— can process colossal amounts of data into analysis and feed into insights, and ultimately aid in rapid decision making. Edge computing is a timely solution that powers and smoothens other tech developments designed to make life better, be it for your health or to drive smoothly.

Who’s interested in this industry? Check out our investments and partnerships in the edge computing space via our incumbent mapping portfolio.