Edge Architecture: How to Process Data in Real-Time to Accelerate Production

Why are companies increasingly choosing IoT devices that can pull data from the most heterogeneous assets? Easy — numbers and values today are indispensable to make decisions and act quickly.

This happens in all work contexts, but in industrial production, processing data in real-time is essential to accelerate processes. This operation can run smoothly when information passes quickly between the machines and the resources responsible.

This is where Edge Computing comes into play: the ability to process data close to the source that produces it. By placing a simple device near a piece of machinery, for example, you can collect data and manage it locally without sending it to the cloud. This reduces latency and circumvents bandwidth limitations.

There are several factors to consider when choosing an Edge Computing solution, and it’s important to examine them before investing.

Reduced bandwidth usage, improved business flexibility, and faster decision-making are the benefits that lead us to choose an Edge architecture over a Cloud-based one. In fact, the difference is simple:

• Edge architecture is decentralized because processing activities occur close to the source. Therefore, the entire process is located in the factory or the appropriate location.
• Cloud Computing is based on a centralized architecture because all data will have to reach the destination server. In this case, information processing can occur outside the company’s network and where production is located.

Is an Edge Computing architecture secure? The answer is in the full article on the DeltalogiX blog.

And to make sure you don’t miss out on new articles, sign up for a free newsletter on the topics of the Internet of Things, Automation, Cyber Security, and Sustainability.

Thanks for reading!