"Our participation in UAO represents another significant step in our commitment to delivering open and flexible solutions based on industry standards, enabling industrial organizations to innovate more rapidly and with reduced risk." - David Purón, CEO at Barbara.

The 181 zettabytes of data generated annually by over 13 billion devices exceeds global internet bandwidth, posing challenges for cloud computing due to high costs, latency, and security concerns. Edge computing processes data locally, offering efficient, secure analysis without constant connectivity. Barbara’s Industrial Edge Management and Orchestration Platform simplifies managing this infrastructure by providing cloud-like capabilities on-premises and bridging the IT-OT gap.

AI EdgeLabs, a next-generation edge cybersecurity solution provider, and Barbara today announced the partnership to guarantee a more secure environment for the clients utilizing Barbara Edge Orchestration platform.

By implementing real-time optimized Machine Learning algorithms at each of its desalination plants, ACCIONA a global infrastructure operator, managed to minimize the use of reactive chemicals, eliminate associated regulatory penalties, and leverage an edge infrastructure to implement new predictive applications for water quality control. In this article, we explore the intricacies of the project.

Many companies find themselves underprepared for the complexities involved in expanding their projects within the Edge. Proof of concepts (POCs) typically focus on one or a few locations, but if successful, they must scale to hundreds or even thousands of locations. This article highlights key considerations for technology leaders navigating the Edge AI landscape.

Despite the vast amount of data collected by the industry in recent years, less than 25% is ever processed. This is often due to enterprises lacking the necessary infrastructure to effectively utilize their data. In this article, we will explore the digital journey of a Power Grid operator, from its initial stages till deploying machine learning at the edge.

One of the most transformative technologies that have emerged in recent years is software containerization, which revolutionizes the way industrial companies develop, deploy, and manage their software solutions. Kubernetes is very useful for large, cloud-dependent workloads like web applications, but it is not optimal for smaller, more industrial-oriented workloads that must operate in complex, isolated environments.‍ In this article we explain why.

Edge Computing is becoming a critical component, enabling organizations to leverage edge data in unprecedented ways. However, embarking on an Edge Computing project can be daunting, as building an edge solution requires significant time, investment, and a highly skilled team.This article explores the essentials for getting started with Edge Computing.

This is the second article in our series exploring the challenges of Digital Transformation in industrial companies on their path to full IT-OT convergence. In this edition, we focus on the Data Journey, the process of transforming raw data into intelligent, AI-driven organization.