Artificial intelligence and machine learning-based monitoring and design of biological wastewater treatment systems

NK Singh, M Yadav, V Singh, H Padhiyar, V Kumar… - Bioresource …, 2023 - Elsevier
Artificial intelligence (AI) and machine learning (ML) are currently used in several areas. The
applications of AI and ML based models are also reported for monitoring and design of …

[HTML][HTML] A critical review for the impact of anaerobic digestion on the sustainable development goals

F Piadeh, I Offie, K Behzadian, JP Rizzuto… - Journal of …, 2024 - Elsevier
Anaerobic Digestion (AD) technology emerges as a viable solution for managing municipal
organic waste, offering pollution reduction and the generation of biogas and fertilisers. This …

Global biogeography and projection of soil antibiotic resistance genes

D Zheng, G Yin, M Liu, L Hou, Y Yang… - Science …, 2022 - science.org
Although edaphic antibiotic resistance genes (ARGs) pose serious threats to human well-
being, their spatially explicit patterns and responses to environmental constraints at the …

Application of machine learning in anaerobic digestion: Perspectives and challenges

IA Cruz, W Chuenchart, F Long, KC Surendra… - Bioresource …, 2022 - Elsevier
Anaerobic digestion (AD) is widely adopted for remediating diverse organic wastes with
simultaneous production of renewable energy and nutrient-rich digestate. AD process …

Syntrophy mechanism, microbial population, and process optimization for volatile fatty acids metabolism in anaerobic digestion

Y Zhang, C Li, Z Yuan, R Wang, I Angelidaki… - Chemical Engineering …, 2023 - Elsevier
The low efficiency and stability of anaerobic digestion (AD) has always hindered its wide
application. The accumulation of volatile fatty acids (VFAs) cause acidification and inhibition …

Application of machine learning methods for the prediction of organic solid waste treatment and recycling processes: A review

H Guo, S Wu, Y Tian, J Zhang, H Liu - Bioresource technology, 2021 - Elsevier
Conventional treatment and recycling methods of organic solid waste contain inherent flaws,
such as low efficiency, low accuracy, high cost, and potential environmental risks. In the past …

Groundwater quality forecasting using machine learning algorithms for irrigation purposes

A El Bilali, A Taleb, Y Brouziyne - Agricultural Water Management, 2021 - Elsevier
Using conventional methods to evaluate the irrigation water quality is usually expensive and
laborious for the farmers, particularly in develo** countries. However, the applications of …

Innovation designs of industry 4.0 based solid waste management: Machinery and digital circular economy

CG Cheah, WY Chia, SF Lai, KW Chew, SR Chia… - Environmental …, 2022 - Elsevier
Abstract The Industrial Revolution 4.0 (IR 4.0) holds the opportunity to improve the efficiency
of managing solid waste through digital and machinery applications, effectively eliminating …

The role of machine learning to boost the bioenergy and biofuels conversion

Z Wang, X Peng, A **a, AA Shah, Y Huang, X Zhu… - Bioresource …, 2022 - Elsevier
The development and application of bioenergy and biofuels conversion technology can play
a significant role for the production of renewable and sustainable energy sources in the …

Predicting the performance of anaerobic digestion using machine learning algorithms and genomic data

F Long, L Wang, W Cai, K Lesnik, H Liu - Water research, 2021 - Elsevier
Modeling of anaerobic digestion (AD) is crucial to better understand the process dynamics
and to improve the digester performance. This is an essential yet difficult task due to the …