AIMC Topic: Recycling

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Sequential treatment of paper and pulp industrial wastewater: Prediction of water quality parameters by Mamdani Fuzzy Logic model and phytotoxicity assessment.

Chemosphere
Recycling of industrial wastewater meeting quality standards for agricultural and industrial demands is a viable option. In this study, paper and pulp industrial wastewater were treated with three biological treatments viz. aerobic, anaerobic and seq...

Classification for plastic bottles recycling based on image recognition.

Waste management (New York, N.Y.)
Recycling of used plastic bottles is an important measure to protect the environment and save energy. Usually, bottles in different colors have different value for recycling. Classification of plastic bottles recycling based on image recognition duri...

Review of water quality criteria for water reuse and risk-based implications for irrigated produce under the FDA Food Safety Modernization Act, produce safety rule.

Environmental research
Questions related to the safety of alternative water sources, such as recycled water or reclaimed water (including grey water, produced water, return flows, and recycled wastewater), for produce production have been largely un-explored at the detail ...

Multilayer Hybrid Deep-Learning Method for Waste Classification and Recycling.

Computational intelligence and neuroscience
This study proposes a multilayer hybrid deep-learning system (MHS) to automatically sort waste disposed of by individuals in the urban public area. This system deploys a high-resolution camera to capture waste image and sensors to detect other useful...

Selection of recycling centre locations by using the interval type-2 fuzzy sets and two-objective genetic algorithm.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
In the sense of contemporary industrial challenges, it may be said that many issues in the field of recycling may be analysed. In this paper, the model for choosing locations for construction of recycling centres equipped with new technology is propo...

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...

Predicting recycling behaviour: Comparison of a linear regression model and a fuzzy logic model.

Waste management (New York, N.Y.)
In this paper we demonstrate that fuzzy logic can provide a better tool for predicting recycling behaviour than the customarily used linear regression. To show this, we take a set of empirical data on recycling behaviour (N=664), which we randomly di...

Automated material flow characterization of WEEE in sorting plants using deep learning and regression models on RGB data.

Waste management (New York, N.Y.)
Waste from electrical and electronic equipment (WEEE) is a rapidly growing waste stream. Notably, electronic equipment contains valuable and critical raw materials. State of the art in WEEE recycling uses a combination of automated comminution and se...

Automated Electro-construction waste Sorting: Computer vision for part-level segmentation.

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