AIMC Topic: Electronic Waste

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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...
Neural Networks, Computer Construction Industry Waste Management Electronic Waste Recycling Automation
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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...
Electronic Waste Support Vector Machine Boosting Machine Learning Algorithms Waste Management Algorithms
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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...
Plastics Polystyrenes Spectrum Analysis, Raman Machine Learning Electronic Waste Recycling
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X-ray transmission imaging of waste printed circuit boards for value estimation in recycling using machine learning.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA Jun 20, 2024
The growing amount of electronic waste is a global challenge: on one hand, it poses a threat to the environment as it may contain toxic or hazardous substances, on the other hand it is a valuable 'urban mine' containing metals like gold and copper. T...
X-Rays Electronic Waste Recycling Machine Learning
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Classification of e-waste using machine learning-assisted laser-induced breakdown spectroscopy.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA May 9, 2024
Waste management and the economy are intertwined in various ways. Adopting sustainable waste management techniques can contribute to economic growth and resource conservation. Artificial intelligence (AI)-based classification is very crucial for rapi...
Alloys Electronic Waste Spectrum Analysis Lasers Waste Management Machine Learning Principal Component Analysis Aluminum
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Prediction of e-waste generation: Application of modified adaptive neuro-fuzzy inference system (MANFIS).

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA Sep 21, 2022
An accurate estimation of generated electronic waste (e-waste) plays a pivotal role in the development of any appropriate e-waste management plan. The present study aimed to exploit modified adaptive neuro-fuzzy inference system (MANFIS) for the esti...
Models, Theoretical Electronic Waste Electronics Iran Fuzzy Logic
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Fuzzy-based adaptive learning network using search and rescue optimization for e-waste management model: case study.

Environmental science and pollution research international Oct 1, 2021
In recent days, the expansion of e-waste disposal should be increased due to environmental hazards, contamination of groundwater, an unconcerned consequence on marine life, human health, and decrease in the fertility of the soil. The majority of the ...
Electronic Waste Refuse Disposal Recycling Waste Management Machine Learning
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Application of deep learning object classifier to improve e-waste collection planning.

Waste management (New York, N.Y.) Apr 28, 2020
This study investigates an image recognition system for the identification and classification of waste electrical and electronic equipment from photos. Its main purpose is to facilitate information exchange regarding the waste to be collected from in...
Humans Deep Learning Electronic Waste Neural Networks, Computer
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How to improve WEEE management? Novel approach in mobile collection with application of artificial intelligence.

Waste management (New York, N.Y.) Mar 2, 2016
In global demand of improvement of electrical and electronic waste management systems, stakeholders look for effective collection systems that generate minimal costs. In this study we propose a novel model for application in mobile collection schemes...
Refuse Disposal Models, Theoretical Poland Electronic Waste Waste Management Recycling Cities Artificial Intelligence
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