Miren Zabaleta

Barbara will adapt the edge computing firmware for Iberdrola´s substation sensorization and automation and will empower third parties to integrate their software solutions driving the future of Iberdrola´s digital grid.

Aduriz Distribución, a prominent electric power distribution company, recognized the pressing need to modernize its operations. In partnership with Barbara, Aduriz embarked on a transformative journey by deploying Edge infrastructure in two low-voltage (LV) substations using Barbara’s Industrial Edge platform. This successful initiative highlights how Aduriz overcame critical challenges, leveraging advanced technology to enhance system performance and deploy intelligence models that drive operational intelligence.

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.

View or webinar on demand "How to Maximize your Edge Data" June 19. Whether you're just starting to collect data and want to maximize its potential or you're deep into your digital transformation journey and aiming to harness AI at the edge, this webinar provides actionable insights applicable to every stage of your enterprise’s edge journey.

As organizations‘ appetite for seizing opportunities at the edge grow, scaling from a single use case in one facility to various uses cases in multiple locations poses a significant challenge. This article highlights the importance of implementing an Edge Management and Orchestration tool to efficiently and securely scale edge computing initiatives.

The food and beverage industry stands on the brink of a new era, driven by the transformative power of Artificial Intelligence in the Edge. By processing data on-site, businesses can immediately adjust operations, predict maintenance issues, and ensure product quality, directly impacting their bottom line. In this article we explore the challenges of embracing Edge AI in the Food 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.

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.

AI enables machines to learn from data, make decisions, and adapt to changing conditions, thereby optimising manufacturing processes to a greater extent. This fusion of automation and AI is transforming the manufacturing industry and driving innovation in ways never seen before.

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.

In the age of AI, the chemical industry finds itself on the brink of a major shift, propelled by the demands for enhanced efficiency, sustainability, and innovation.‍ Edge AI emerges as a key technological enabler, offering unparalleled capabilities for real-time monitoring and control, predictive maintenance, supply chain management, and enhancing sustainability and energy waste optimization.

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.