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Artificial intelligence for waste management in smart cities: a review
The rising amount of waste generated worldwide is inducing issues of pollution, waste
management, and recycling, calling for new strategies to improve the waste ecosystem, such …
management, and recycling, calling for new strategies to improve the waste ecosystem, such …
Applicability and limitation of compost maturity evaluation indicators: A review
Y Kong, J Zhang, X Zhang, X Gao, J Yin… - Chemical Engineering …, 2024 - Elsevier
Composting is a resource treatment method that uses aerobic microorganisms to convert
organic solid waste into stable humus and applied as organic fertilizer. The maturity …
organic solid waste into stable humus and applied as organic fertilizer. The maturity …
Machine-learning intervention progress in the field of organic waste composting: Simulation, prediction, optimization, and challenges
L Huang, J Hou, H Liu - Waste Management, 2024 - Elsevier
Aerobic composting stands as a widely-adopted method for treating organic solid waste
(OSW), simultaneously producing organic fertilizers and soil amendments. This biologically …
(OSW), simultaneously producing organic fertilizers and soil amendments. This biologically …
Artificial intelligence and machine learning for smart bioprocesses
In recent years, the digital transformation of bioprocesses, which focuses on
interconnectivity, online monitoring, process automation, artificial intelligence (AI) and …
interconnectivity, online monitoring, process automation, artificial intelligence (AI) and …
From waste to wealth: Innovations in organic solid waste composting
M Xu, H Sun, E Chen, M Yang, C Wu, X Sun… - Environmental …, 2023 - Elsevier
Organic solid waste (OSW) is not only a major source of environmental contamination, but
also a vast store of useful materials due to its high concentration of biodegradable …
also a vast store of useful materials due to its high concentration of biodegradable …
Machine learning applications for biochar studies: A mini-review
Biochar is a promising carbon sink whose application can assist in reducing carbon
emissions. Development of this technology currently relies on experimental trials, which are …
emissions. Development of this technology currently relies on experimental trials, which are …
Prediction models for bioavailability of Cu and Zn during composting: Insights into machine learning
B Bai, L Wang, F Guan, Y Cui, M Bao, S Gong - Journal of Hazardous …, 2024 - Elsevier
Bioavailability assessment of heavy metals in compost products is crucial for evaluating
associated environmental risks. However, existing experimental methods are time …
associated environmental risks. However, existing experimental methods are time …
[HTML][HTML] An artificial intelligence approach for identification of microalgae cultures
In this work, a model for the characterization of microalgae cultures based on artificial neural
networks has been developed. The characterization of microalgae cultures is essential to …
networks has been developed. The characterization of microalgae cultures is essential to …
Machine learning for sustainable organic waste treatment: a critical review
Data-driven modeling is being increasingly applied in designing and optimizing organic
waste management toward greater resource circularity. This study investigates a spectrum of …
waste management toward greater resource circularity. This study investigates a spectrum of …
Synergistic improvement of humus formation in compost residue by fenton-like and effective microorganism composite agents
JZ Cai, YL Yu, ZB Yang, XX Xu, GC Lv, CL Xu… - Bioresource …, 2024 - Elsevier
Improving the humification of compost through a synergistic approach of biotic and abiotic
methods is of great significance. This study employed a composite reagent, comprising …
methods is of great significance. This study employed a composite reagent, comprising …