Industry at the Edge posts

When implementing a data-based strategy, it all starts with the Data. One of the typical sources to extract data are IoT devices. Knowing which IoT communication protocols exist and how to use them for data communication is essential as they are the ones that make data gathering from them possible.

As organizations' appetite for seizing opportunities at the edge grows, data-driven industries must carefully select the right infrastructure to seamlessly scale from initial implementations to large-scale deployments across multiple facilities.This article explores why an Edge Management and Orchestration tool is essential for efficiently and securely scaling edge computing initiatives.

For industrial companies embracing AI, understanding the MLOps workflow is key to turning use cases into real-world results. In this post, we show how Barbara integrates seamlessly into each stage of the workflow especially where the edge plays a critical role.

Edge AI brings machine learning capabilities directly to edge devices, allowing real-time data processing and decision-making at the source without relying on cloud connectivity. This unlocks faster, smarter, and more autonomous operations across the shop floor. In this article we explore the challenges of embracing Edge AI in the Food & Beverage Industry.

The integration of Artificial Intelligence (AI) in automotive manufacturing is not a new concept. However, the shift towards the Edge where AI algorithms operate on the data generated at the source rather than being sent to a centralised server, is a game-changer. In this article we explore the main challenges of embracing Edge AI and why moving AI to the edge brings unprecedented levels of efficiency, safety, and sustainability to car manufacturers.

In industrial manufacturing, the cement industry is notable for its considerable environmental impact and high energy usage. Amid increasing environmental concerns and a drive towards sustainability, edge computing presents innovative solutions to improve supply chain efficiency, sustainability, energy conservation, and product traceability.