Advanced Single-View Image-Based Framework for Volume Estimation in Urban Solid Waste Management

Efficient solid waste management is crucial to making cities clean and sustainable environments. This paper presents a methodology composed of well-established algorithms for volume estimation in urban solid waste management using single-view images. The proposed system is built upon state-of-the-art model-based algorithms, including instance segmentation, depth estimation, and point cloud–based volume calculation. The methodology demonstrates the capability to accurately estimate the volume of both single and multiple plastic bags containing urban solid waste. We evaluated our approach using real-world data. Numerical results indicate that the proposed system is promising even in complex scenarios. Despite challenges such as manual distance rescaling and limited datasets, the system shows considerable potential for further refinement and enhancement toward scenarios as complex as real urban environments. The proposed methodology contributes to advancing management technologies for smart cities.