Grid Optimizer and DTU Compute (Danish Technical University – Department of Applied Mathematics and Computer Science) will collaborate on a project with the objective of using DTU’s world-class research in providing machine learning based picture and video recognition for optimizing some of the most costly technical work processes in planning and designing grids (fiber, electricity, water, etc).
The project will develop an application that will be integrated into the Grid Optimizer machine learning engine. The application will analyze detailed pictures and videos taken by drones in order to automate the validation of grid design quality and costs. Significant cost savings for infrastructure establishment can be expected for utilities by providing real-life, detailed update of business cases through the application. Currently these design validations are done manually, or not done at all. The application will use machine learning to obtain the grid specific competences required and standard drones with standard camera technology to capture the required picture and video data input.
Please contact Lars Struwe Christensen at Grid Optimizer for more information and details.