AIMC Topic: Waste Management
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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 ...
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...
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 ...
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...
A sustainable industrial waste control with AI for predicting CO2 for climate change monitoring.
Journal of environmental management
Apr 23, 2025
As the challenge of climate change continues to grow, we need creative solutions to predict better and track industrial waste carbon emissions, focusing on sustainable waste management practices. The present study proposes a state-of-the-art Metavers...
Predicting and investigating water quality index by robust machine learning methods.
Journal of environmental management
Apr 3, 2025
This study addresses the critical challenges of waste management and water quality in urban environments, where accelerated urbanization has exacerbated environmental degradation and public health risks. Employing advanced machine learning algorithms...
Reducing food waste in the HORECA sector using AI-based waste-tracking devices.
Waste management (New York, N.Y.)
Mar 1, 2025
This study assesses the effectiveness of an intervention employing an AI-based, fully automatic waste-tracking system for food waste reduction in HORECA establishments. Waste-tracking devices were installed in a restaurant within a holiday resort and...
Enhancing e-waste management: a novel light gradient AdaBoost support vector classification approach.
Environmental monitoring and assessment
Feb 27, 2025
The global consequences of electronic waste significantly affect the environment and human health. Accurate classification is essential for effective recycling and management to mitigate serious environmental harm caused by improper disposal. However...
Classification and predictive leaching risk assessment of construction and demolition waste using multivariate statistical and machine learning analyses.
Waste management (New York, N.Y.)
Feb 19, 2025
Managing construction and demolition waste (CDW) poses serious concerns regarding landfilling and recycling because of the potential release of hazardous elements after leaching. Ceramic materials such as bricks, tiles, and porcelain account for more...
Trustworthy and Human Centric neural network approaches for prediction of landfill methane emission and sustainable waste management practices.
Waste management (New York, N.Y.)
Jan 30, 2025
Landfills rank third among the anthropogenic sources of methane gas in the atmosphere, hence there is a need for greater emphasis on the quantification of landfill methane emission for mitigating environmental degradation. However, the estimation and...
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