Artificial intelligence for industry 4.0: Systematic review of applications, challenges, and opportunities

Z Jan, F Ahamed, W Mayer, N Patel… - Expert Systems with …, 2023 - Elsevier
Many industry sectors have been pursuing the adoption of Industry 4.0 (I4. 0) ideas and
technologies, which promise to realize lean and just-in-time production through digitization …

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 …

Livestock and poultry farm wastewater treatment and its valorization for generating value-added products: Recent updates and way forward

S Vaishnav, T Saini, A Chauhan, GK Gaur… - Bioresource …, 2023 - Elsevier
Livestock and poultry wastewater poses a potent risk for environmental pollution
accelerating disease load and premature deaths. It is characterized by high chemical …

An integrated first principal and deep learning approach for modeling nitrous oxide emissions from wastewater treatment plants

K Li, H Duan, L Liu, R Qiu… - Environmental …, 2022 - ACS Publications
Mathematical modeling plays a critical role toward the mitigation of nitrous oxide (N2O)
emissions from wastewater treatment plants (WWTPs). In this work, we proposed a novel …

Development of a wide-range soft sensor for predicting wastewater BOD5 using an eXtreme gradient boosting (XGBoost) machine

PML Ching, X Zou, D Wu, RHY So, GH Chen - Environmental Research, 2022 - Elsevier
In wastewater monitoring, detecting extremely high pollutant concentrations is necessary to
properly calibrate the treatment process. However, existing hardware sensors have a limited …

Forecasting heterogeneous municipal solid waste generation via Bayesian-optimised neural network with ensemble learning for improved generalisation

ZX Hoy, KS Woon, WC Chin, H Hashim… - Computers & Chemical …, 2022 - Elsevier
Future projections of municipal solid waste (MSW) generation trends can resolve data
inadequacy in formulating a sustainable MSW management framework. Artificial neural …

Modeling biogas production from anaerobic wastewater treatment plants using radial basis function networks and differential evolution

D Karamichailidou, A Alexandridis… - Computers & Chemical …, 2022 - Elsevier
This study presents a new method for modeling biogas production obtained from anaerobic
digestion treatment plants with increased accuracy. The method is based on artificial neural …

Machine learning models for inverse design of the electrochemical oxidation process for water purification

Y Sun, Z Zhao, H Tong, B Sun, Y Liu… - … Science & Technology, 2023 - ACS Publications
In this study, a machine learning (ML) framework is developed toward target-oriented
inverse design of the electrochemical oxidation (EO) process for water purification. The …

Dynamic Domino Effect Assessment (D2EA) in tank farms using a machine learning-based approach

MT Amin, GE Scarponi, V Cozzani, F Khan - Computers & Chemical …, 2024 - Elsevier
The current work presents a Dynamic Domino Effect Assessment (D2EA) methodology for
chemical storage tank farms. While the application of the proposed approach is focused on …

Using LSTM neural network based on improved PSO and attention mechanism for predicting the effluent COD in a wastewater treatment plant

X Liu, Q Shi, Z Liu, J Yuan - Ieee Access, 2021 - ieeexplore.ieee.org
Enhancing the monitoring capabilities of wastewater treatment plant (WWTP) key features
can accomplish accurate prediction to help WWTPs develop a plan, which is of great …