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Electronic Waste

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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.)
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...

Application of deep learning object classifier to improve e-waste collection planning.

Waste management (New York, N.Y.)
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...

Fuzzy-based adaptive learning network using search and rescue optimization for e-waste management model: case study.

Environmental science and pollution research international
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 ...

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
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...

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
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...

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
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...

Raman spectroscopy integrated with machine learning techniques to improve industrial sorting of Waste Electric and Electronic Equipment (WEEE) plastics.

Journal of environmental management
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...

Enhancing e-waste management: a novel light gradient AdaBoost support vector classification approach.

Environmental monitoring and assessment
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...