AIMC Topic: Industrial Waste
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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...
Unlocking the potential of Eudrilus eugeniae in mitigating the pollution risk of pesticides and heavy metals: Fostering machine learning tactics to optimize environmental health.
The Science of the total environment
Mar 8, 2025
Agro-industrial waste management remains a critical challenge in sustainable development, particularly due to contamination with heterogeneous micropollutants such as heavy metals (HMs), pesticides, and polyphenols. This study explores an innovative ...
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...
Optimizing papermaking wastewater treatment by predicting effluent quality with node-level capsule graph neural networks.
Environmental monitoring and assessment
Jan 18, 2025
Papermaking wastewater consists of a sizable amount of industrial wastewater; hence, real-time access to precise and trustworthy effluent indices is crucial. Because wastewater treatment processes are complicated, nonlinear, and time-varying, it is e...
Machine learning-based automated waste sorting in the construction industry: A comparative competitiveness case study.
Waste management (New York, N.Y.)
Jan 8, 2025
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 ...
Enzymes from Fishery and Aquaculture Waste: Research Trends in the Era of Artificial Intelligence and Circular Bio-Economy.
Marine drugs
Sep 10, 2024
In the era of the blue bio-economy, which promotes the sustainable utilization and exploitation of marine resources for economic growth and development, the fisheries and aquaculture industries still face huge sustainability issues. One of the major ...
Prediction of COD in industrial wastewater treatment plant using an artificial neural network.
Scientific reports
Jun 14, 2024
In this investigation, the modeling of the Aksaray industrial wastewater treatment plant was performed using artificial neural networks with various architectures in the MATLAB software. The dataset utilized in this study was collected from the Aksar...
Predicting the Occurrence of Substituted and Unsubstituted, Polycyclic Aromatic Compounds in Coking Wastewater Treatment Plant Effluent using Machine Learning Regression.
Chemosphere
May 28, 2024
Organic contaminants such as polycyclic aromatic compounds (PACs) occurring in industrial effluents can not only persist in wastewater but transform into more toxic and mobile, substituted heterocyclic products during treatment. Thus, predicting the ...
Agro-industrial waste management employing benefits of artificial intelligence.
Environmental science and pollution research international
May 7, 2024
By 2050, the world's population is predicted to reach over 9 billion, which requires 70% increased production in agriculture and food industries to meet demand. This presents a significant challenge for the agri-food sector in all aspects. Agro-indus...
Artificial intelligence-based prediction model for the elemental occurrence form of tailings and mine wastes.
Environmental research
Feb 2, 2024
With the advent of the second industrial revolution, mining and metallurgical processes generate large volumes of tailings and mine wastes (TMW), which worsens global environmental pollution. Studying the occurrence of metal and metalloid elements in...
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