AIMC Topic: Waste Management

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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.)
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 ...

Enhancing door-to-door waste collection forecasting through ML.

Waste management (New York, N.Y.)
We explore the application of machine learning (ML) techniques to forecast door-to-door waste collection, addressing the challenges in municipal solid waste (MSW) management. ML models offer a promising solution to optimize waste collection operation...

The development of a waste management and classification system based on deep learning and Internet of Things.

Environmental monitoring and assessment
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.)
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.)
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-...

Turning trash into treasure: Exploring the potential of AI in municipal waste management - An in-depth review and future prospects.

Journal of environmental management
Rapid urbanization, economic expansion, and population growth have increased waste generation in many nations worldwide. Research on municipal waste management (MWM) is moving towards new frontiers in efficiency and applicability due to the growing a...

Assessment of type and quantities of food and beverage plastic packaging: A case study.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
Plastic pollution has been identified as one of the most pressing environmental issues of the 21st century, driven by excessive consumption and inadequate plastic waste management. This issue is particularly reflected in short lifespan of plastic pro...

Recent advances in dark fermentative hydrogen production from vegetable waste: role of inoculum, consolidated bioprocessing, and machine learning.

Environmental science and pollution research international
Waste-centred-bioenergy generation have been garnering interest over the years due to environmental impact presented by fossil fuels. Waste generation is an unavoidable consequence of urbanization and population growth. Sustainable waste management t...

ONDL: An optimized Neutrosophic Deep Learning model for classifying waste for sustainability.

PloS one
Sustainability has become a key factor on our planet. If this concept is applied correctly, our planet will be greener and more eco-friendly. Nowadays, waste classification and management practices have become more evident than ever. It plays a cruci...

A hybrid classification and evaluation method based on deep learning for decoration and renovation waste in view of recycling.

Waste management (New York, N.Y.)
The escalating volume of decoration and renovation waste (D&RW) amid the rapid urbanization in China has posed significant challenges for the effective recycling of this waste stream, primarily due to the difficulty of accurately assessing its precis...