AIMC Topic: Recycling
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Machine learning-based automated waste sorting in the construction industry: A comparative competitiveness case study.
Waste management (New York, N.Y.)
Jan 8, 2025
This article presents a comparative analysis of the circularity and cost-efficiency of two distinct construction material recycling processes: ML-based automated sorting (MLAS) and conventional sorting technologies. Empirical data was collected from ...
Raman spectroscopy integrated with machine learning techniques to improve industrial sorting of Waste Electric and Electronic Equipment (WEEE) plastics.
Journal of environmental management
Jan 3, 2025
Current industrial separation and sorting technologies struggle to efficiently identify and classify a large part of Waste of Electric and Electronic Equipment (WEEE) plastics due to their high content of certain additives. In this study, Raman spect...
An explainable machine learning system for efficient use of waste glasses in durable concrete to maximise carbon credits towards net zero emissions.
Waste management (New York, N.Y.)
Dec 31, 2024
Recycling waste glass (WG) can be time-consuming, costly, and impractical. However, its incorporation into concrete significantly reduces environmental impact and carbon emissions. This paper introduces machine learning (ML) to civil engineering to o...
AI-driven identification of a novel malate structure from recycled lithium-ion batteries.
Environmental research
Dec 27, 2024
The integration of Artificial Intelligence (AI) into the discovery of new materials offers significant potential for advancing sustainable technologies. This paper presents a novel approach leveraging AI-driven methodologies to identify a new malate ...
Do circular innovations and carrying capacity of natural environment enhance circular economy in the European Union? Evidence from simulation and machine learning methods.
Journal of environmental management
Dec 27, 2024
The longevity of the natural environment is fundamental for sustainable production and consumption. The circular economy conserves natural resources, ensures sustainable production and consumption, and protects the natural environment. The role of ci...
The development of a waste management and classification system based on deep learning and Internet of Things.
Environmental monitoring and assessment
Dec 26, 2024
Waste sorting is a key part of sustainable development. To maximize the recovery of resources and reduce labor costs, a waste management and classification system is established. In the system, we use Internet of Things (IoT) and edge computing to im...
ECCDN-Net: A deep learning-based technique for efficient organic and recyclable waste classification.
Waste management (New York, N.Y.)
Dec 19, 2024
Efficient waste management is essential to minimizing environmental harm as well as encouraging sustainable progress. The escalating volume and sophistication of waste present significant challenges, prompting innovative methods for effective waste c...
AI-based plastic waste sorting method utilizing object detection models for enhanced classification.
Waste management (New York, N.Y.)
Dec 16, 2024
The export ban on plastic waste by China has brought domestic plastic recycling to the forefront of environmental concerns, with sorting being a crucial step in the recycling process. This study assessed the performance of advanced AI models, Mask R-...
Design of Recyclable Plastics with Machine Learning and Genetic Algorithm.
Journal of chemical information and modeling
Dec 3, 2024
We present an artificial intelligence-guided approach to design durable and chemically recyclable ring-opening polymerization (ROP) class polymers. This approach employs a genetic algorithm (GA) that designs new monomers and then utilizes virtual for...
Modelling and evaluation of mechanical performance and environmental impacts of sustainable concretes using a multi-objective optimization based innovative interpretable artificial intelligence method.
Journal of environmental management
Nov 16, 2024
This study focuses on modelling sustainable concretes' mechanical and environmental properties with interpretable artificial intelligence-based automated rule extraction, management of waste materials, and meeting future prospects. In this context, 2...
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