Miren Zabaleta

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.

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 our on-demand webinar "How to Maximize your Edge Data". 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.

AI empowers machines to learn from data, make smarter decisions, and adapt in real time, driving unprecedented efficiency in manufacturing. The convergence of AI and automation is reshaping the industry and accelerating innovation. In this article, we explore how organizations can successfully embark on their Edge AI journey.

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.

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.

Barbara and Gridfy have joined forces to bring AI Flexibility algorithms to the Edge.‍‍ Gridfy has developed and implemented the AI flexibility algorithm located in one of Cuerva´s substations while Barbara has provided the Edge Infrastruicture that deploys and orchestrates Artificial Intelligence at the Edge.

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.

The virtualization of electrical equipment is becoming a game changer. By decoupling hardware from software, organizations can unlock significant advantages, from cutting costs and reducing maintenance to boosting safety. In this article, we explore the key benefits and challenges of virtualizing substations and how this approach is transforming the way critical infrastructure is managed.

We are back at ENLIT Europe 2023, to showcase how Transmission and Distribution System operators can improve their operations by virtualizing HV, MV and LV substations and add intelligence to their assets with Edge AI Technology.