David Purón

According to Gartner, 13% of organizations implementing IoT projects already use digital twins, while 62% are planning or establishing them. Despite this growth, industrial sectors like energy, water infrastructure, and process manufacturing face challenges in adopting digital twin solutions. This article explores potential solutions.

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.

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.

In this evolving digital landscape, Quantum-related technologies are gaining significant attention in recent years in the field of cybersecurity. Understanding how quantum random number generators can bolster security at the edge is great news for any company concerned about protecting data integrity and confidentiality in an increasingly complex environment.

The use of AI in Edge Computing opens up exciting opportunities across industries, offering benefits like real-time decision-making, low latency inferencing, and enhanced data security. However, quantifying these benefits and demonstrating tangible returns on investment remains a challenge for many companies.‍

At Barbara, we believe that industry transformation can not be accomplished by a single company. Our view is of a Community of AI developers, hardware manufacturers, industrial system integrators and other technology partners, that join forces with us to make the most of our technology so that we can altogether respond with a comprehensive solutions to the most complex problems.

When we talk about "water sustainability", experts use some fundamental indicators. For us, the most important is the resilience of their infrastructures, i.e. how prepared they are for adverse situations, and the efficiency of their processes, measured as the number of resources to be invested in meeting a specific demand. AI plays a fundamental role in these processes.

Artificial Intelligence (AI) is the greatest catalyst for technological innovation in history, with countless applications in the energy sector. Key examples are the optimisation of production and storage, smart market trading, consumer savings and efficient consumption models for reducing carbon footprints, among others.

As the market moves from proof of concepts to large multi-application deployments that require scalability, different technological alternatives emerge at the Edge. In this article, we explore the foundation for a successful Edge Computing project.

Edge computing, or the ability to store and process data on servers close to the source or destination of that data, is becoming increasingly fashionable. The IT world has been using it for years with regional data centers that serve content more efficiently. What is new today is the beginning of its incursion into industrial environments.

Industrial IoT is transforming the way plant environments operate by enabling hyper-connected networks that provide value through smart factories, predictive maintenance, energy management, remote monitoring, and more. This technology empowers industries to optimize productivity, increase efficiency, and reduce costs.