Estimativa Volumétrica de Resíduos Sólidos Urbanos em Imagem de Visualização Única.

Abstract

Efficient solid waste management is crucial for keeping the city clean and sustainable. This work presents a methodology that uses well-established algorithms for volume estimation in urban solid waste management from single-view images. The proposed system is based on state-of-the-art computer vision concepts and models, including instance segmentation, depth estimation, and volume calculation based on point clouds. The methodology demonstrated the ability to accurately estimate the volume of both individual and multiple solid waste objects in images. We evaluated our approach using real-world data. Despite challenges such as manual rescaling of distances and limited datasets, our system shows considerable potential for refinement and improvement, targeting complex scenarios like real urban environments. Numerical results indicated that the proposed system is promising even in complex scenarios, with mean absolute percentage errors (MAPE) of 8.60% for single waste and 9.23% for multiple wastes, resulting in an overall average of 8.91%. The coefficient of determination was 95.11% for single instances and 87.64% for multiple instances. The proposed methodology significantly contributes to the advancement of management technologies in smart cities.