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Bold Awards

Infoassets – StreetView grid mapping

Improving data collection for the low-voltage electricity grid, with computer vision and AI to process images collected from road vehicles and satellite sources
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The InfoAssets project, led by E-REDES, was developed to address inefficiencies and high costs associated with collecting data on the low-voltage (LV) electrical grid. Traditionally, this data was gathered by technical teams in the field, leading to time-consuming and expensive processes. The lack of an updated asset registry negatively impacted processes such as maintenance, planning, and customer connections.

Problem Solved

The absence of a comprehensive and up-to-date grid asset registry limited operational efficiency and responsiveness. Field surveys were required to obtain critical data such as geolocation, network topology, and connection conditions, resulting in high costs and long execution timelines.

Technology Used

The project leveraged cutting-edge technologies, including:

  • Computer Vision: Applied to process imagery of the electrical grid captured by ground vehicles, supplemented by satellite images.
  • Artificial Intelligence (AI): Algorithms trained using data classified by specialized technicians to interpret and automate the analysis of infrastructure.
  • Integration with GIS Systems: Delivering detailed information on user-friendly platforms ready for immediate use.

The solution automated the identification of grid components (poles, conductors, equipment) and network layouts, differentiating them from other infrastructures, such as telecommunications. This level of automation positions E-REDES as a global pioneer in applying these technologies to LV networks.

Innovative Features

The project disruptively combines advanced AI and computer vision technologies, which are rarely applied so comprehensively in utility services. Its standout features include:

  1. Full Automation: Automatically recognizing most grid assets.
  2. Scalability: Capable of widespread implementation without significant manual intervention.
  3. Sustainability: Substantial reduction in CO₂ emissions by minimizing fieldwork.

Additionally, the project established a robust, scalable database, paving the way for future use cases, such as assessing the condition of grid equipment and improving maintenance planning.

Benefits and Key Numbers

  • Efficiency: The automated process reduced data collection costs by ~30%, addressing an activity previously costing tens of millions of Euros annually.
  • Improved Processes: The updated registry accelerates new customer connection processes by providing precise network layouts and accurate distance estimates.
  • Environmental Impact: Reduced emissions by limiting on-site field operations.
  • Investment: €4.5 million.
  • Technology Involved: AI, Big Data/Analytics, and Robotics.

In summary, InfoAssets is a groundbreaking project that not only resolves critical operational challenges but also sets a new benchmark in technological innovation and sustainability within the utility sector.

Projects evaluation criteria

Level of Impact
40%
Scalability
30%
Transparency
20%
H-Factor
10%

PUBLIC VOTES

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VOTES

Pedro
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Fazila
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Ana
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Luis Angel
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Kley
9.75
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José Luis
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Joao
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Lopes
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Rita
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Michael
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Nuno
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Joao
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