eneida DeepGrid®

Eneida’s solutions for the Electric Grid follow an architecture that has the DeepGrid® IoT Platform as its core:

  • Receives and processes data from smart sensors (Data Analytics)

  • Manages the entire system (events, assets and smart sensors)

  • Provides all the information to web clients through its REST API

  • Integrates with several corporate subsystems

Smart devices specifically designed for each solution

  • Easy and quick installation

  • Robust and compact

  • Processing and memory capacities

  • Several communication technologies

  • Firmware updated remotely

Rich web interfaces that enable you to Visualize and Manage the electric grid assets from anywhere.

  • Dashboard with geographic representation of assets with events

  • Global vision of the system

  • Real-time events and recommendations: get notified of any relevant change instantaneously

  • Detailed description of events: know exactly what is happening with your assets

  • Follow maintenance operations with a multi-state events resolution process

  • Follow the time evolution of the relevant physical variables

  • Graphical representation of continuous variables

  • Analyse historical data, as well as current real-time data

  • Detailed data for a finer analysis

  • Useful filter tools to help getting the most of it

  • Follow assets condition state. Any changes are perceived immediately.

  • Register and manage assets and devices

  • Remote configuration of devices

  • Consult assets and devices details and historical data (events, recommendations, sensors data)

  • Schedule maintenance interventions

DeepGrid® builds its decision support – Events and Recommendations  – on top of a Data Analytics module

State of the art Machine Learning algorithms take the most from data to give you deeper and valuable information about your electric grid assets:

  • Anomaly Detection

  • Predictive Maintenance

  • Smart Object Detection for Surveillance Systems

DeepGrid® is always learning to improve

  • New data is used to Retrain and Improve the Machine Learning Algorithms

  • Future Recommendations are even better

  • The electric grid assets performance and condition are always optimized

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