Suppliers Spain Barbara
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Barbara

Barbara is the Edge AI Platform for the industry sector. Barbara helps Machine Learning Teams manage the lifecycle of models in the Edge, at scale. Now companies can deploy, run, and manage their models remotely, in distributed locations, as easily as in the cloud.
Spain
2017
Private
< $10m
11 - 50
Open website

Barbara is the Edge AI Platform for organizations looking to overcome the challenges of deploying AI, in mission-critical environments.

With Barbara companies can deploy, train and maintain their models across thousands of devices in an easy fashion, with the autonomy, privacy and real- time that the cloud can´t match.

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Barbara´s technology is composed of:

• Industrial Connectors to attach edge devices to any other legacy or next-generation equipment.

• Edge Orchestrator to deploy and control container-based and native edge apps across thousands of distributed locations.

• Device Management to provision, configure, update, operate and decommission Edge Devices cybersecurely.

• MLOps to optimize and package your trained model in minutes.

• Marketplace of containerized Edge applications ready to be deployed. The marketplace includes third-party applications and a suite of Barbara Microservices.

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Barbara customer base extends across various sectors, including Electrical Power Grids/Smart Grids, Water Utilities, Chemical Manufacturing, Oil and Gas, Industrial Machinery Manufacturing, Process Manufacturing, Infrastructure Operations, and Maritime Transport.

 

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Barbara is a provider of Industrial IoT platform as a service (paas) technologies, and also active in the agriculture, electrical grids, oil and gas, renewable energy, and utilities industries.
Technologies
Platform as a Service (PaaS)
Edge Computing Platforms
Use Cases
Demand Planning & Forecasting
Digital Twin
Edge Computing & Edge Intelligence
Mesh Networks
Predictive Maintenance
Functions
Business Operation
Logistics & Transportation
Maintenance
Industries
Agriculture
Electrical Grids
Oil & Gas
Renewable Energy
Utilities
Services
Software Design & Engineering Services
Barbara ’s Technology Stack maps Barbara ’s participation in the platform as a service (paas) IoT technology stack.
  • Application Layer
  • Functional Applications
  • Cloud Layer
  • Platform as a Service
    Infrastructure as a Service
  • Edge Layer
  • Automation & Control
    Processors & Edge Intelligence
    Actuators
    Sensors
  • Devices Layer
  • Robots
    Drones
    Wearables
  • Supporting Technologies
  • Analytics & Modeling
    Application Infrastructure & Middleware
    Cybersecurity & Privacy
    Networks & Connectivity
Technological Capability
None
Minor
Moderate
Strong
Number of Case Studies3
Edge Computing: Automatic fine-tuning of predictive models in water plants
ACCIONA spent significant time and resources manually testing water samples in a laboratory to determine chemical concentrations. Due to the time it took to obtain these results, they were often outdated and unreliable. This resulted inadditional costs related to chemical supply and regulatory penalties.By implementing real-time optimized Machine Learning control algorithms at each of its desalination plants, ACCIONA was able to minimize the use of reactive chemicals, eliminate associated regulatory penalties, and provide an efficient edge infrastructure to implement new applications for predictive maintenance, energy efficiency, sensing, optimization or reinforcement learning.
Edge AI: Deploying AI Flexibility in a Virtualized LV/ MV Substation
Cuerva a Spanish Grip Operator, was seeking to enhance grid knowledge through the implementation of the AI Energy Forecasting Model to obtain precise forecasts of user demand and energy generation.Cuerva’s grid encompasses over 16,000 diverse supply points, making cloud-based operations intricate and susceptible to issues such as connectivity loss, delays in information transmission, and reliance on centralized infrastructure, which can result in the loss of critical data.To tackle these challenges, the Edge technology has proven to be the sole alternative capable of addressing these issues effectively. It ensures real-time data access and operates in a decentralized manner, minimizing the impact of device failures on the overall functionality of the network.In this successful case, we illustrate how with Barbara DSOs can implement AI directly in substations to accurately predict the demand and production values of consumers linked to the transformation center where an Edge node run by Barbara has been deployed.
Edge Computing in Substations
Cuerva Distribution needed to have real-time data (<1 minute) from the line cells of its substations and fault detectors in order to obtain instant alerts regarding supply quality: surges or drops in voltages or intensity, neutral currents, etc. Traditionally, all these data are processed through SCADA, a rather rigid system which does not allow for custom events and alarms to be configured. Due to software limitations, it took around 15 minutes for the data to transfer from SCADA to a database.
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