Waste management refers to the process of collecting, transporting, processing, and disposing of waste materials in an efficient and safe manner.
The goal of waste management is to minimize the amount of waste produced, reduce the negative impact of waste on the environment and human health, and conserve natural resources by recovering valuable materials from waste.
What We Do
rProcess is involved in object segmentation and annotation of dumpster and waste materials (paper, plasti, metals, construction & organics) as per clients’ specific requirements. Clients apply machine learning and use this data to differentiate waste from recyclable and non-recylable materials.
We are also involved in analyses of
- Robotic waste sorting performance on its accuracy rate, error rate and efficiency
- Dumpster/Bin Analyses that involves analysing the contents of a dumpster or waste container to gain insights into the waste generation patterns of a particular facility or community.
Types of Waste Management
Semantic segmentation is a computer vision technique that involves dividing an image into multiple segments or regions, each of which is assigned a label that describes the content of that region
Bounding box segmentation, also known as object detection, is a computer vision technique that involves detecting and localizing objects in an image by drawing a rectangular bounding box around each object.