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Water management

Machine Learning at the Edge to optimise chemical usage in water plants

The monitoring and operation processes of a water network have traditionally been carried out using sensors and SCADAs, but they are largely operator-dependent. Given the criticality and the volumes of data handled, infrastructure managers are now running advanced algorithms at the edge. In this article, we explore the real case of deploying Machine Learning at the Edge to optimise chemical control processes in real time.

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The Benefits of Virtualizing Electrical Substations

Companies are increasingly interested in virtualizing electrical equipment because it offers a range of benefits for their operations. Firstly, virtualization reduces the need for physical infrastructure, which can result in cost savings, reduced maintenance requirements, and increased safety. In this article we talk about Electrical Substations and the benefits of separating hardware and software.

Smart Grid

Cloud vs Edge: Where Should I Deploy My Application

In recent years, the debate between Cloud and Edge Computing has been a hot topic in the world of technology. While both technologies have their advantages and disadvantages, it can be challenging to determine which one is the best option for your application. In this article, we will take a closer look at both, their benefits and drawbacks, and ultimately answer the question: Cloud vs Edge, where should I deploy my application?

Barbara

Barbara featured at STL Partners' Top 2023 Edge Computing Companies

This year, STL Partners asked companies to provide more information on their financial milestones associated with edge computing, as well as for details on the practicalities of edge applications that they are enabling. By doing so, the firm was able to chart the increase in maturity of edge offerings, with more companies seeing significant revenue streams coming from their edge portfolio.

Barbara

Machine Learning at the Edge to optimise chemical usage in water plants

The monitoring and operation processes of a water network have traditionally been carried out using sensors and SCADAs, but they are largely operator-dependent. Given the criticality and the volumes of data handled, infrastructure managers are now running advanced algorithms at the edge. In this article, we explore the real case of deploying Machine Learning at the Edge to optimise chemical control processes in real time.

Water management

What is MLOps and what are the advantages of using it in the Edge?

In this article you will learn what MLOps is and what are the advantages of using it on the Edge. Discover how this development and operations methodology for machine learning can help you improve the efficiency and accuracy of your machine learning models in edge computing environments.

Technology

Smart Water: real-time monitoring and control using Edge Nodes

To operate more efficiently, water management operators face the challenge to monitor in a unified and comprehensive way all components that make up the OT and industrial automation architectures. The use of Edge Nodes allows connectivity with different equipment in each installation regardless of the various data reporting equipment. Discover how utility companies can access sophisticated intelligence to support water operators using Edge Computing.

Water management
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Resources

Industrial Energy Efficiency Plan 2023

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How Edge Computing is changing the Industrial sector

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The state of cybersecurity in industry (only available in Spanish)

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