I+D+i
30/01/26 - Europe/Madrid

Follow-up to the CO2 MASTER project

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"COMPUTER VISION SYSTEM WITH DRONE FOR THE GEOMETRIC CHARACTERIZATION OF MATERIAL VOLUMES IN LINEAR WORK AND MINIMIZATION OF THE CARBON FOOTPRINT ASSOCIATED WITH ITS TRANSPORT"

ROVER INFRASTRUCTURES advances in the execution of the MASTER CO2 project, an advanced computer vision system with a drone for the volumetric modeling of materials used in large linear works. This allows the automation of the calculation of cubicage of materials coming from slopes, in order to optimize the transports to minimize their associated carbon footprint. This initiative is part of ROVER’s ethical and environmental commitment to carry out its construction activity in a sustainable way, motivated by the reduction of GHG emissions, with the ecological transition being one of its fundamental pillars.

Supported by the Valencian Institute for Competitiveness and Innovation IVACE+i, with a total budget of 510,650 € co-financed by the European Union with ERDF funds, the MASTERCO2 system is to be implemented with the participation of ONTHEFLADS (OTF), a software development company specializing in innovative AI-based solutions and the implementation of advanced image recognition applications.

During the first year of the project, data acquisition fieldwork by drone with equipped sensors has been carried out on the region of interest in road works and railway platform, using for this, the latest technology in computer vision. In addition, the design and technical specifications of the graphical user interface have been carried out. In the next year, work will be carried out on the development and integration of computer tools for data processing, implementation of algorithms and validation of the system, which is scheduled to end in December 2026.

The project represents a breakthrough in sustainability, computational vision and transportation in civil engineering, betting on the technological development of novel solutions that contribute to reducing the carbon footprint throughout the life cycle of the infrastructure, as well as the optimization of activities that contribute to its ecological transition and digital transformation.

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