Unique capabilities of edge computing in IoT

  • Articles
  • Apr 21,25
IoT edge computing projects allow people to benefit from advantages associated with both technologies, letting them tap into many unique capabilities, says Emily Newton.
Unique capabilities of edge computing in IoT

IoT applications have become widespread throughout many industries, including electronics and other engineering fields. Many of those efforts also involve edge computing. IoT edge computing projects allow people to benefit from advantages associated with both technologies, letting them tap into many unique capabilities. What are some of the most compelling reasons to consider edge computing in IoT use cases? 

1. Enhanced real-time data collection and processing 
Edge computing moves data processing capabilities closer to the source, reducing the time required to convert that information into an interpretable format. Industrial leaders strongly prefer speedy processing times for IoT applications that collect urgent information and notify people accordingly.

The processing speed is one reason why it is common to use edge computing in IoT applications for health care. One example occurred when a research team collected patients’ biosignal data with a connected pulse oximeter. Then, medical professionals could review the data in real time, giving them the information needed to make critical care decisions. 

This study’s experiments involved five pulse oximeters and one edge node, making it a limited investigation. However, the researchers envisioned rolling out their innovation to various hospital areas, significantly increasing patient visibility on a large scale. Other industries also require current, reliable data. Fortunately, IoT edge computing applications can meet that requirement, equipping professionals to act faster and more confidently. 

2. Reduced latency
Latency concerns the time required for data to pass from one point to another. Applying edge computing to IoT devices or applications can significantly minimise latency. Minor delays are not problematic in some applications, but everyone who has experienced lag during video calls knows it can cause frustration. However, latency can be dangerous in some cases, such as self-driving cars.

Consider a case of such vehicles moving at approximately 75 miles per hour. Then, 1 millisecond of round-trip latency translates to more than 2 inches between two moving vehicles. That example shows shortening latency time frames as much as possible is critical for making autonomous automobiles safe and widely adopted.

Other IoT edge computing applications also benefit from lower latency. Whether decision-makers use the technologies in transportation, utilities or process industries, they always appreciate fewer delays and better efficiency. 

3. Improved compatibility with complementing technologies
Using edge computing in IoT applications can create opportunities for electronics engineers and others working on these projects to explore other technologies that help them meet specific goals. Many people interested in one type of advanced tech are open to seeing how others align with their efforts.

One example is mobile edge computing, which some people use as an alternative to the cloud. Predictions indicate this option will comprise three-quarters of enterprise-driven data processing by 2025. Transitions to 5G networks will lead that transition, and many familiar with that next-generation infrastructure intend to use IoT devices on it.

Additionally, since edge computing brings processing capabilities closer to connected products, it supports individuals who want to use augmented reality for mission-critical reasons, such as improving quality control or reducing errors in manufacturing plants.

4. Elevated trust among reluctant adopters 
Even as IoT edge computing solutions have become more popular, some people have waited to embrace them. That hesitation often occurs due to concerns about the unknown. Many individuals prefer to keep using what they know despite the availability of potentially superior possibilities. Such feelings are usually more common within groups that have waited longer than others to apply connected technologies to their work. 
 
Farmers are good examples because many have worked for decades without the connected crop-spraying, soil-monitoring and harvesting technologies now on the market. One executive familiar with the matter said edge computing is essential to the automated and connected equipment that some agricultural professionals have begun using as they explore the IoT.

Many worry about data breaches, wondering if cybercriminals will steal proprietary information, adversely affecting their competitiveness for the season and beyond. However, edge computing keeps the information within a farmer’s local network, reducing the chances of unauthorized parties accessing it.

Additionally, IoT edge computing deployments are increasingly straightforward, improving the confidence of people newer to such technologies or who have limited resources and cannot create massive infrastructure to support their tech needs. 

Raised awareness of edge computing in IoT products 
These advantages emphasize why people who develop or use IoT products should strongly consider how edge computing could promote better outcomes. Interested parties should also stay informed of how their peers rely on these two technologies since such examples could give them valuable insights and inspiration.

About the author:
Emily Newton is a tech and industrial journalist and the Editor-in-Chief of Revolutionized magazine. Subscribe to the Revolutionized newsletter for more content from Emily.

Image Courtesy: www.freepik.com

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