AIMC Topic: Recycling

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Towards sustainable solutions: Effective waste classification framework via enhanced deep convolutional neural networks.

PloS one Jun 4, 2025
As industrialization and the development of smart cities progress, effective waste collection, classification, and management have become increasingly vital. Recycling processes depend on accurately identifying and restoring waste materials to their ...
Convolutional Neural Networks Recycling Waste Management Neural Networks, Computer Deep Learning
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Automated Electro-construction waste Sorting: Computer vision for part-level segmentation.

Waste management (New York, N.Y.) May 19, 2025
The global generation of construction, demolition, and renovation (CDR) waste has surged, increasing the demand for efficient recycling solutions. Emerging technologies can automate the sorting of CDR waste, which is crucial for specialised categorie...
Recycling Waste Management Electronic Waste Neural Networks, Computer Construction Industry Automation
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Plastics detection and sorting using hyperspectral sensing and machine learning algorithms.

Waste management (New York, N.Y.) May 1, 2025
Plastic waste second life management requires effective detection (and sorting if necessary) techniques to tackle the environmental challenge it poses. This research explores the application of hyperspectral imaging in the spectral range 900-1700 nm ...
Remote Sensing Technology Plastics Algorithms Principal Component Analysis Recycling Waste Management Discriminant Analysis Hyperspectral Imaging Machine Learning Refuse Disposal
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Zero-shot and few-shot multimodal plastic waste classification with vision-language models.

Waste management (New York, N.Y.) Apr 23, 2025
The construction sector is a large consumer of plastic, generating substantial volumes of plastic waste. Effective recycling of this waste requires accurate classification, as different plastic materials undergo distinct recycling processes to retain...
Plastics Recycling Construction Materials Waste Management
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Efficient and anti-interference plastic classification method suitable for one-shot learning based on laser induced breakdown spectroscopy.

Chemosphere Apr 15, 2025
Efficient recycling of plastics is critical for environmental sustainability. In this work, an efficient and anti-interference method for plastic classification based on one-shot learning and laser-induced breakdown spectroscopy (LIBS) was proposed. ...
Spectrum Analysis Neural Networks, Computer Lasers Algorithms Recycling Plastics
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Identifying plastic materials in post-consumer food containers and packaging waste using terahertz spectroscopy and machine learning.

Waste management (New York, N.Y.) Feb 18, 2025
Accurate identification of plastic materials from post-consumer food container and packaging waste is crucial for enhancing the purity and added value of recycled materials, thereby promoting recycling and addressing the issue of plastic pollution. H...
Machine Learning Terahertz Spectroscopy Recycling Food Packaging Bayes Theorem Polyethylene Terephthalates Plastics
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A machine-learning approach to optimize nutritional properties and organic wastes recycling efficiency conversed by black soldier fly (Hermetia illucens).

Bioresource technology Feb 17, 2025
Suboptimal nutrition in organic waste limits the growth of black soldier fly (BSF) larvae, thereby reducing biowaste recycling efficiency. In this study, weight gain data from BSF larvae fed diets with distinct nutrient compositions were used to buil...
Machine Learning Waste Products Larva Diptera Animals Animal Feed Simuliidae Recycling Biomass
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Contaminant detection in flexible polypropylene packaging waste using hyperspectral imaging and machine learning.

Waste management (New York, N.Y.) Feb 10, 2025
Flexible plastic packaging (FPP) constitutes one of the largest post-consumer plastic streams processed in recycling facilities. To address the key challenges of its sorting and quality control, this study developed and tested a classification proced...
Recycling Product Packaging Spectroscopy, Fourier Transform Infrared Principal Component Analysis Machine Learning Hyperspectral Imaging Polypropylenes
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Identification and information acquisition of high-value construction solid waste combined millimeter-wave radar and convolutional neural networks.

Waste management (New York, N.Y.) Jan 27, 2025
The accumulation of construction solid waste (CSW) leads to the waste of land resources and environmental pollution, becoming a significant social problem. Identifying the amount of high-value CSW is essential for assessing the value of accumulated C...
Recycling Solid Waste Radar Convolutional Neural Networks Neural Networks, Computer Construction Materials Algorithms
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Prototype of AI-powered assistance system for digitalisation of manual waste sorting.

Waste management (New York, N.Y.) Jan 25, 2025
Global waste generation is projected to reach 3.40 billion tons by 2050, necessitating improved waste sorting for effective recycling and progress toward a circular economy. Achieving this transformation requires higher sorting intensity through inte...
Waste Management Machine Learning Recycling Artificial Intelligence
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