2019 and 2020 are the years of emerging technology — artificial intelligence (AI), edge computing, and the Internet of Things (IoT) are all transforming the very fabric of modern society. Of course, these three technologies are juggernauts in their own right, but when you start combining them together in a variety of applications, they really propel each other to new heights.
As sensor technology and IoT develop, they produce more and more data to store, scrub, and analyze. But a cloud burgeoning with mountains of data every day isn’t going to be so fast in helping analysts and data scientists make sense of the data.
That’s where edge computing comes in. Boston-based International Data Corporation predicts that, by 2020, 45% of all data generated by IoT devices will be stored, processed, analyzed, and acted upon at the edge, or close to the edge, of a network.
Edge Computing Basics
20 years ago, cloud computing was a dream; there was no stable infrastructure to support it. However, things have changed; the dream has now become the standard. With today’s faster Internet speeds, smaller computers, and bigger consumer markets, businesses can’t afford to play catch-up. They must remain on the edge of technology adoption and innovation.
Simply put, edge computing moves analysis from a remote server to your local device. Edge computing can also use locally-generated data, from RFID tags, barcode scanners, and other tools to inform the data analysis. It can use data stored in the cloud, but it’s not necessary: since edge computing carries out the computation on the device itself, the result is almost instant.
We can combine edge computing with cloud computing for an enhanced solution that is fast for use in training algorithms. These cloud-trained algorithms can then be used on the edge to make better-informed decisions using weeks or months of data as a reliable source.
One of the best things about edge computing is that it doesn’t require an Internet connection to function. There’s no need for enterprises to plan for power and network outages, poor Internet connections, or keeping operations going in inclement weather.
Tech’s Potential Depends on Edge Computing
To fuel the future, edge computing is an inevitability. As long as we keep producing data, edge computing acts as a relief technology to help us manage data more easily.
In edge computing, the physical computation system is placed at the edge of the network, where the data is getting generated. This improves speed, efficiency, and even electricity bills for large applications.
Many experts argue that IoT will never reach its full potential if it doesn’t have edge computing supplementing it. In situations where split-second decisions are being made, like in autonomous driving or remote surgery, any latency in the cloud during calculations and analysis could mean the difference between life and death.
Edge computing offers real-time results, lower latency, and powerful flexibility — it can be incorporated into almost any IoT application in almost any industry. Other industries that will especially love edge computing’s benefits include retail, industrial, finance, and remote office branch office.
Computing the Future
For example, in retail, inventory, sales, and security can all be handled seamlessly across multiple brick-and-mortar stores and e-commerce shops. Location-based data will help target customers with in-store ads and coupons at just the right time.
Similarly, banks require quick analyses on credit scores for loan applications, data sharing between branches, and handling of larger business transactions. Processing this type of data is heavy on modern-day tools, but edge computing can handle it easily.
To fully replace the data centers we use to store, scrub, and analyze data today, we must ensure edge computing brings reliability to the system. Edge computing must also be easy to implement, flexible in how it gets incorporated into an existing system, self-healing, and most of all, affordable.
Data centers right now are resilient, scalable, available, secure, and manned with IT professionals. Although it took years to reach this point, we don’t have much time for trial and error with edge computing. However, without sufficient safety systems and automation built in to self-correct any human-caused errors, edge computing could prove difficult to roll-out.
In data centers, even if hardware fails, there is already software written to shift payloads onto back-up hardware. These are the types of fail-safe features that edge computing needs.
Edge of Tomorrow
When we consider businesses that have hundreds of locations, thousands of employees and devices, and an international customer base, edge computing must be easy to implement and affordable. The more complex an enterprise’s operations and systems, the more time it will take to implement, deploy, and manage edge computing.
Unfortunately, as we know all too well, technology takes years to decrease in price while simultaneously growing in performance. And human management in edge computing is a big deal; if possible, edge computing should run seamlessly without many helping hands. If management or maintenance needs to occur, it should be possible for a skilled expert to do it easily and remotely.
As more and more enterprises deploy edge computing systems to their operations, we’re excited to see the innovative ways various companies use this technology to tackle their unique problems. With edge computing, almost anything is possible in IoT.Tags: app development Boston, Boston app developer, boston app developers, Boston IoT app developer, Boston IoT app developers, Boston IoT app development, cloud computing, custom app development, edge computing, enterprise IoT applications, enterprise level IoT applications, internet of things, iot, IoT app developer, iot app development, mobile app development