How Edge Computing is Making its Mark in the IoT Industry

Edge Computing

The IoT world is becoming smarter, faster and more intuitive with each passing day. With technological advancements and innovation, industrial companies are beginning to drive new levels of performance and productivity using IoT solutions. And edge computing is quickly proving to be a key element to these Industry 4.0 breakthroughs.

What is Edge Computing?

Edge computing is transferring the logic that is typically performed on the cloud back to the devices, themselves, through gateways. This enables analytic and data gathering to occur directly at the source, the device.

In the past, edge devices were very weak, so depending on devices to perform logic wasn’t realistic. But devices today are being designed with stronger hardware capabilities. This allows for the installation of full operating systems directly on the devices. It also makes it possible to attain logic directly on the device, instead of on the cloud via the Edge.

Advantages of Edge Computing

There are several reasons why edge computing is considered more advantageous than cloud-based computing.

  1. Real-time responses. Situations that call for real-time responses would be better off using edge computing compared to cloud-based computing. For example, edge computing can be seen in smart homes and smart security domains where real-time responses are needed. If someone breaks into a house, the owner wouldn’t want to depend on cloud-based response times, rather he would need immediate response time, which the Edge offers. For factory use cases, real-time responses are needed to immediately deal with any problems or issues that might arise and avoid a larger crisis.
  2. Battery & network cost saving. Another use case in favor of the Edge is when saving battery life and networking is recommended, where data sent to the cloud will be limited. An example of this involves GPS devices. With GPS devices, limiting the data that is being sent to the cloud and save battery life and networking is key, so the data is only updated if it’s relevant or involves a big change in the GPS location.
  3. Privacy. Privacy is another huge reason to choose edge computing over cloud-based computing. There are times when sensitive information wouldn’t want to be sent to the cloud, so it’s stored on a private network and kept confidential. Performing logic directly on the device eliminates the need to open an additional connection to the cloud, keeping the sensitive information more secure.


A New Way to Store Information

Over the past couple of years, most businesses have incorporated cloud-based storage into their IoT solutions in order to monitor and analyze the gathered data from the devices. The cloud will still continue to be used, but with the introduction of devices that have bundling capabilities – computing, storing and analyzing – edge computing is gaining traction in the industry.

And with edge computing, the data can be stored in two locations. First, on the device itself. When the device has the ability to apply logic on the data, the data can also be stored there as well. This is especially advantageous with cases that require real-time responses, battery saving, and privacy matters.

The second place data can be stored is on the cloud as a backup. There might be specific logic that is relevant to several devices, so data also needs to be stored on the cloud in order to compare the collected data to other use cases that already exist there. Many times, edge computing and cloud-based computing can work together in a coexisting environment.

Industrial Benefits of The Edge

The business side of edge computing also presents a compelling case for its successful future. As devices become smarter, IoT solutions also become smarter and faster, helping businesses to gain a higher value and ROI for their investment:

  • Predictive Management. Utilizing the Edge can help businesses reduce costs and add an extra layer of security assurance.
  • Energy Efficient. Not only does the Edge lower energy consumption and maintenance costs, it is highly reliable and increases smart manufacturing.
  • Time Saving. Because logic is performed directly on the device, this allows for time saving measures and rapid deployment of new processes and models, essentially scaling IoT solutions much quicker.


Edge Computing Use Case

There are quite a few examples of edge computing already being successfully implemented.

One example is autonomous vehicles. With autonomous cars literally running on hundreds of sensors that generate over 40TB of data for every eight hours of driving, it makes perfect sense to use edge computing. It’s not practical or safe to send all that information to the cloud. This is a real-time response case, where every millisecond of data requires immediate attention to ensure the safety of passengers and the public.

And although this data requires real-time response, the cloud is also an important factor as well. Analyzing the data and comparing it to the performance of other cars already in existence is essential for the future of autonomous vehicles. It’s a classic case for the Edge and cloud-based computing working together in unison.

Living on The Edge

As more and more industries start applying smart devices and smart IoT solution to their products, the demand for “smarter, faster and better “ is inevitable. Edge computing is just another step toward the future of IoT, and it’s receiving more and more traction by many large companies.

If you’re interested in learning more about The Edge and IoT Solutions, contact one of our IoT experts today.

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