Photo of Halden City by Night
THE AI HUB
eSmart Systems is a technology driven company with a strong focus on research and development, and with applied AI at its core. Over the past few years, eSmart Systems has for example developed the product Connected Drone, a software system for mapping and inspecting power line components. Connected Drone makes extensive use of technologies such as deep learning to automate the health assessment of power transmission and distribution assets. Detection and assessment of rust on power masts, woodpecker damage on wooden poles, insulator defects such as cracks, contamination, or flashing are only a few examples of key defects that power companies need to identify through inspections. The automated analyses of inspection data can be done in virtual real time when images are collected, or when uploading images from archives, and is the first step toward the vision of an intelligent asset management system for predictive and risk-based network maintenance.
The way we work with artificial intelligence, and specifically machine learning, is by aggregating and leveraging data to learn and build different typologies of models, such as predictive models, classification models, object detection models etc. that, through our products, provide tangible value to our customers. Where sufficient field data is not available or is too expensive to collect, we also resort to the generation of so called "synthetic data", such as images collected from a simulation environment where relevant equipment and assets have been modeled and rendered. Synthetic data allows us to train AI models that can more reliably recognize uncommon types of assets and infrequent typologies of defects.
With technologies like machine learning and artificial intelligence we at eSmart see that the energy industry has a great opportunity to analyze their data and find out exactly which areas they need to invest in or do maintenance on. In addition, this technology brings significant opportunities for optimization of the grid and investment and operating costs savings of up to 20-40% over time.
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