Every business today that we witness today are working with heaps and pools of data in some kind or the other. Turning that data into valuable insights is the most demanding process for organisations to bring better transformation. In fact, the Global IP traffic as estimated by Cisco is pacing up to for a growth of 3.3 zettabytes annually by 2021. This directly means, in the coming years and as technology advances, businesses have to find their ways to utilize the data in the best way.
Though this data is a big enabler for businesses, as it piles up in volume and velocity, transmitting it for processing becomes untamable trouble. Innovations in technology, such as edge computing, was hence born.
Around for a while now, edge computing refers to decentralizing the processing power of networks, bringing it as close to the source as possible. As a result of this arrangement, data doesn’t need to travel across storage networks.
By doing so, edge computing reduces the backhaul traffic to the central data repository, pacing up data processing by manifolds.
Why Edge Computing?
The speed at which data generates will never slow down. In fact, it’s only going to see an upward trend by the day. As a result, businesses will be heavily relying on technologies like edge computing, in the future.
An IDC research predicts that in 3 years, 45% of IoT-created data will be stored, processed, analyzed, and acted upon close to, or at the edge of the network. The research also points out that 6 billion devices will be connected to edge computing solutions.
By bringing in ‘decentralization’ to cloud networks, edge computing has added to the many advantages that businesses can reap from data.
For example, disruptions can be limited to only one point in the entire network. Consider that there is a cyberattack that leads to a power outage. With edge computing, you can curb its impact on only the local applications rather than letting it spread through the entire network. That’s just one use case. Every industry can benefit tremendously from edge computing.
Listed below are a few use cases detailing on how industrial edge computing can transform their business processes with this new-age technology.
Improved customer experience
When data can be processed right at the source, marketers can configure automation to respond to customer requirements, queries, and other inputs instantly. To top this, with edge computing, immediate data processing has become a possibility. Therefore, onsite reactions to the action that a customer takes, happen even before a customer leaves the site, or closes the tab.
Data such as customer’s location, previous onsite interactions, etc. can all be processed in real-time for hyper-personalized interactions, at a flash of light. The tremendous speed and relevancy of data-based interactions ultimately result in significantly enhanced customer experience.
Increased data privacy
Businesses today deal not just with high volumes of data but also with how sensitive and prone all this data has become to cyber-attacks. The number and complexity of online crimes have been on an upswing. In fact, businesses state that data privacy and security have become one of the biggest concerns.
Edge computing helps businesses address these security concerns. It does so by increasing the data bandwidth and achieving a low latency. But in addition, edge computing also helps businesses become a 100% GPR compliant. This means that businesses that use edge technology will always work towards fulfilling all data privacy and security norms, even as they change with the industry.
Enhanced augmented reality capabilities
Both augmented and virtual reality are highly dependent on their local environment. Most VR tools need to understand and scan the environment around them.
Though data can be stored on the cloud for AR and VR, translating it into vivid and fast experiences can be challenging. Imagine watching an AR clip where the tech is interrupted because data couldn’t be retrieved and processed at the required pace. Edge computing makes sure that never happens.
AR and VR are extensively being deployed in eCommerce too. Brands like Nordstorm have succeeded in creating visually immersive experiences that give shoppers a real-like, in-store experience. However, the solutions behind such technology are rarely looked into. That’s where edge computing lies.
Improvement in autonomous vehicles
Self-driving cars run on data. But, because they are running in real life, it becomes all the more important for them to process all the data, faster. They should be efficient enough to learn things without having to reach out to the cloud for data processing.
Engines need to run even when there is limited or no connectivity to the cloud. Coordinating with other vehicles on the road without having to ask the cloud or a remote server, estimating weather conditions and analyzing jams, everything requires smarter processing with solutions like edge computing.
Think about what would happen if an autonomous vehicle running on a congested road isn’t able to gauge the nearest approaching vehicle. The probability of accidents would increase due to the lack of efficient data processing.
Other than the above-mentioned areas, edge computing is also being tremendously leveraged in industrial IoT. This is one aspect of edge computing that we’ll be delving into in detail.
How Industrial IoT can benefit from Edge Computing
Let’s go back to the point in this post where we talked about edge computing ‘decentralizing’ cloud networks. Now, where most people think that cloud computing and industrial edge computing are two very distinct approaches, we say they are not. Edge computing rather enhances cloud computing. But what’s wrong with cloud computing as a stand-alone approach?
- There are data security threats related to IoT that can’t be handled using a traditional cloud-based approach
- There are performance issues related to augmented technologies, such as in the case of cloud-based lighting that we mentioned in the smart buildings use case.
- As the amount of data that you use, process, and share increases the cost related to the cloud also grows leaps and bounds.
All these challenges can be met when you bring in the best of cloud and edge computing to use them together. In cloud computing, data can be generated and stored in the cloud—for instance, your favourite Netflix series! With industrial edge computing, this data can be generated and processed closest to the source, using machines or robots, all across the globe over the world!
While the benefits of edge computing enhanced cloud computing are clear, businesses are still using them in isolation. As per the Automation World survey, more than 50% of the respondents have deployed cloud computing, and nearly 45% are using IoT edge computing for IoT implementations.
‘Manufacturers’ in the survey respondents report that utilizing these technologies they have reaped tremendous benefits in their initial IoT deployments. As per the survey:
- 50% of the companies launching edge/fog or cloud computing IIoT initiatives report significant reductions in downtime.
- 38% report improvements to production output
- 37% tout profitability increases
- 30% highlight a decrease in production costs
If standalone, cloud and edge computing can achieve so much, what amazing results can be achieved when they are combined!
In fact, this marriage is much needed for futuristic IoT deployments that follow a typical rollout pattern.
The pattern consists of phases in which phase one is concerned with the cloud to host core enterprise analytics applications. The next step is to invest in new-age computing technologies such as intelligent automation systems that bring in personalization, real-time communication, and speed of execution in the entire process.
An example to describe the combined real power cloud and edge computing could be about offshore wind turbines. Consider an offshore wind turbine farm that uses cloud computing for its business operations. The cloud aggregate signals about weather conditions. If edge computing is used alongside, critical adjustments can be made to individual wind turbines, such as automatically fine-tuning turbine speeds for optimal fleet performance.
Edge computing has revolutionized the way innovative technology works, bringing in added speed to operations. This is *the* technology that IoT demands.
As requirements and demands out of technology increase, the trend of using cloud computing along with edge computing will get pushed further. Combining cloud and edge computing for IoT implementation spells your betterment.
Think your business needs to get edge computing or cloud computing to its technology stack? Get in touch with the AWS cloud service provider experts at Rapyder today!