abstract
- This project presents a method for estimating the volume of diverse types of scrap in a metal industry terrain with new electromobility technologies and tools. The approach utilizes drones that can be employed in many applications that help develop technologies such as three-dimensional modeling, photogrammetry, and segmentation algorithms powered by deep learning. The proposed solution was implemented using geographic information software and an open-source development, comparing volumetry results that consider the terrain slope, yielding precise results with the help of integrating mathematical and geometrical concepts such as Delaunay triangulation and barycentric coordinates. This method has a direct impact on the accuracy of volumetry in irregular scrap terrains, automating calculation processes and allowing better waste management strategies, reducing costs, and optimizing production process planning for industries, taking advantage of the opportunities electromobility presents. © 2024 IEEE.