Research on the Application Effectiveness of Artificial Intelligence in Empowering Automatic Waste Recycling Machines

Abstract

With the deepening of environmental awareness and the concept of circular economy, the waste recycling industry is undergoing a transformation towards intelligence and automation. This study takes artificial intelligence (AI) technology as the core and analyzes its application efficacy in automated waste recycling machines. Experiments show that the classification accuracy of a deep learning-based image recognition model exceeds 92%. The average daily processing capacity of a single machine has increased by 170%, the purity of resource recycling has improved by 12 - 18%, and each machine can reduce carbon emissions by 1.2 tons annually. Through case studies in Chongqing, Shanghai, and at an enterprise, it has been verified that AI technology possesses universality and industrial synergy effects, addressing the pain points of traditional models. Although the initial equipment investment has increased by 35%, the investment payback period can be controlled within 2.8 years. Based on this, the study proposes recommendations such as strengthening the research and development of multi-modal data fusion technology, promoting the deployment of lightweight and efficient models, and constructing a full-chain intelligent recycling system. In the future, the integration of AI with other technologies can be explored, and cross-disciplinary collaborative innovation can be strengthened. This study provides theoretical support for the industrialization of intelligent recycling equipment and holds significant practical guiding value for promoting the construction of "zero-waste cities" and achieving the "dual carbon" goals.