Artificial intelligence for the circular economy : better waste recovery for sustainable development

Abstract

In contrast to the linear model of "extract, produce, consume, and dispose," the circular economy is based on a model of "extract, produce, consume, and valorize." It involves the reutilization of goods and materials with the goal of simultaneously reducing the exploitation of limited resources, waste generation, and environmental pollution. In this context, the waste treatment process aims to manage and dispose of waste safely and sustainably.

Furthermore, the enhancement of waste treatment processes' quality is notably reliant on artificial intelligence tools. This reliance stems from the utilization of computer algorithms and machine learning, which enable tasks of high risk, for instance. This technology can contribute to enhancing waste sorting efficiency, minimizing contamination, and increasing the quantity of recyclable materials.

The theoretical framework of this article is underpinned by an epistemological stance rooted in the interpretive paradigm, coupled with the application of an inductive mode of reasoning. This methodological approach allows us to delve deeply into the concepts and theories within our field of study